Dynamic Systems and Control

Sistem compressor merupakan salah satu peralatan penting dalam industri proses yang digunakan untuk meningkatkan tekanan gas agar dapat digunakan pada tahapan proses berikutnya. Dalam pengoperasiannya, parameter pressure dan temperature harus dijaga tetap stabil untuk menjamin keamanan, efisiensi, dan kestabilan sistem. Ketidakstabilan tekanan dan temperatur dapat menyebabkan penurunan performa proses, peningkatan konsumsi energi, hingga kerusakan peralatan. Penelitian ini bertujuan untuk merancang sistem instrumentasi dan melakukan simulasi kontrol pressure serta temperature pada compressor menggunakan metode PID (Proportional Integral Derivative) dan optimasi parameter berbasis AI sederhana. Simulasi dilakukan menggunakan MATLAB Simulink dengan konfigurasi open loop dan closed loop untuk menganalisis karakteristik respon sistem berdasarkan parameter rise time, overshoot, settling time, steady-state error, dan disturbance response. Hasil simulasi menunjukkan bahwa sistem closed loop menggunakan PID controller memiliki performa yang lebih baik dibandingkan open loop karena mampu mempercepat respon sistem, mengurangi steady-state error, serta meningkatkan kestabilan pressure dan temperature terhadap perubahan beban operasi. Selain itu, implementasi AI sederhana berbasis regresi linear mampu membantu optimasi parameter PID sehingga overshoot menjadi lebih kecil, settling time lebih singkat, dan respon sistem menjadi lebih stabil dibandingkan tuning PID konvensional. Berdasarkan hasil penelitian, kombinasi PID controller dan AI sederhana dapat menjadi metode yang efektif untuk meningkatkan performa sistem kontrol pressure dan temperature pada compressor industri.

Sistem compressor merupakan salah satu peralatan penting dalam industri proses yang digunakan untuk meningkatkan tekanan gas agar dapat digunakan pada tahapan proses berikutnya. Dalam pengoperasiannya, parameter pressure dan temperature harus dijaga tetap stabil untuk menjamin keamanan, efisiensi, dan kestabilan sistem. Ketidakstabilan tekanan dan temperatur dapat menyebabkan penurunan performa proses, peningkatan konsumsi energi, hingga kerusakan peralatan. Penelitian ini bertujuan untuk merancang sistem instrumentasi dan melakukan simulasi kontrol pressure serta temperature pada compressor menggunakan metode PID (Proportional Integral Derivative) dan optimasi parameter berbasis AI sederhana. Simulasi dilakukan menggunakan MATLAB Simulink dengan konfigurasi open loop dan closed loop untuk menganalisis karakteristik respon sistem berdasarkan parameter rise time, overshoot, settling time, steady-state error, dan disturbance response. Hasil simulasi menunjukkan bahwa sistem closed loop menggunakan PID controller memiliki performa yang lebih baik dibandingkan open loop karena mampu mempercepat respon sistem, mengurangi steady-state error, serta meningkatkan kestabilan pressure dan temperature terhadap perubahan beban operasi. Selain itu, implementasi AI sederhana berbasis regresi linear mampu membantu optimasi parameter PID sehingga overshoot menjadi lebih kecil, settling time lebih singkat, dan respon sistem menjadi lebih stabil dibandingkan tuning PID konvensional. Berdasarkan hasil penelitian, kombinasi PID controller dan AI sederhana dapat menjadi metode yang efektif untuk meningkatkan performa sistem kontrol pressure dan temperature pada compressor industri.

Sistem compressor merupakan salah satu peralatan penting dalam industri proses yang digunakan untuk meningkatkan tekanan gas agar dapat digunakan pada tahapan proses berikutnya. Dalam pengoperasiannya, parameter pressure dan temperature harus dijaga tetap stabil untuk menjamin keamanan, efisiensi, dan kestabilan sistem. Ketidakstabilan tekanan dan temperatur dapat menyebabkan penurunan performa proses, peningkatan konsumsi energi, hingga kerusakan peralatan. Penelitian ini bertujuan untuk merancang sistem instrumentasi dan melakukan simulasi kontrol pressure serta temperature pada compressor menggunakan metode PID (Proportional Integral Derivative) dan optimasi parameter berbasis AI sederhana. Simulasi dilakukan menggunakan MATLAB Simulink dengan konfigurasi open loop dan closed loop untuk menganalisis karakteristik respon sistem berdasarkan parameter rise time, overshoot, settling time, steady-state error, dan disturbance response. Hasil simulasi menunjukkan bahwa sistem closed loop menggunakan PID controller memiliki performa yang lebih baik dibandingkan open loop karena mampu mempercepat respon sistem, mengurangi steady-state error, serta meningkatkan kestabilan pressure dan temperature terhadap perubahan beban operasi. Selain itu, implementasi AI sederhana berbasis regresi linear mampu membantu optimasi parameter PID sehingga overshoot menjadi lebih kecil, settling time lebih singkat, dan respon sistem menjadi lebih stabil dibandingkan tuning PID konvensional. Berdasarkan hasil penelitian, kombinasi PID controller dan AI sederhana dapat menjadi metode yang efektif untuk meningkatkan performa sistem kontrol pressure dan temperature pada compressor industri.

Security issues continue to dominate Nigerian political space and academic discourse. In recent years, the increase in jail breaks has been alarming. To say that the custodial centers of the Nigerian Correctional Service are under siege is not an overstatement. This fact has been corroborated by ubiquitous cases of jailbreaks/prison breaks witnessed over the years. Jailbreak is a threat to national security because it reinforces criminality in the society. Therefore, this calls for quick policy drive to stem the tide with utmost alacrity. The change in the name from Nigerian Prisons Service, to Nigerian Correctional Service, appears to have done nothing to change the narrative of persistent attacks resulting in jailbreaks. This work situates that prevention of jailbreak is another method of counter terrorism/insurgency; therefore, some immediate actions such as interventions to change the conditions of infrastructure, training, and welfare packages need urgent attention. The work observes that there cannot be effective measures to counter insecurity if those in custodial centers/prisons are not reformed, and lack safe custody through constant security breaches, among others. Findings reveal that while insecurity is recipe for attacks on the custodial centers of the Nigerian Correctional Service, the aftermath of such incidents further compound the condition of insecurity in the society. All security agencies operate in the spirit of division of labor, therefore, whatever bad news that affects one agency has negative effects on all others. That is why there is a need for all agencies to be given equal attention, in order to effectively contain insecurity once and for all. Data are elicited though primary and secondary sources. Primary sources are core documents available within the domain of the Nigerian Correctional Service, and included policy documents, and government publications. Their selection was based on relevance, authenticity, official nature, and direct connection to national security. Secondary sources used are published and unpublished materials. They include books, journal articles, theses and dissertations, newspapers, scholarly materials from the internet related to prison, terrorism, criminality and national security. These materials were sourced from online academic databases, credible media platform, among others. All data spawned have also been subjected to critical examination and assessment for the purpose of objectivity.

Finding case studies that give statistical significance to the conclusions of research on Water Distribution Systems (WDS) can be a challenging task. The generation of synthetic (virtual) WDSs has been proposed recently to tackle this difficulty. These methods try to generate realistic data, based on different assumptions for different properties of the networks. This paper describes the use of a new method for the generation of synthetic distribution systems and its subsequent comparison against real life systems to validate the suitability of the synthetic set to drive the conclusions of future research. Focus was given to connectivity and reliability-related indexes considering the future use of these synthetic WDSs to study relationships between connectivity, reliability and energy consumption. The algorithm for the generation of synthetic WDSs was based on the work, methods and software presented by Mair et al. [1]. The procedure can be summed up in 3 steps: 1. Generation of network layouts based on the street patterns of real life cities, 2. Location of demand nodes and sources, 3. Realistic pipe sizing that accounts for non-optimal designs. The validation procedure was made by evaluating metrics or indexes that account for network connectivity [2] and system reliability [3] and comparing their ranges in both sets. Early results showed that the synthetic WDSs required an enhancement of network connectivity to make them more similar to real-life systems. After implementing a routine to increase the meshedness of the networks, an acceptable degree of similarity between the synthetic and the real-life sets of WDSs was achieved, although some modifications to the networks may be required in the future.

Current understanding of ecosystem responses to global warming remains predominantly anchored in elementprocess descriptions that focus on species distributions, phenological shifts, and productivity changes. While substantial empirical evidence documents warming-induced alterations across biological scales, existing frameworks exhibit fundamental limitations in explaining and predicting the widespread occurrence of abrupt ecological changes, regime shifts, and irreversible transitions. This paper argues that global warming, at its thermodynamic essence, constitutes a sustained injection of additional energy into the Earth's ecosystems accompanied by amplified energy fluctuations across multiple temporal scales. Ecosystems, as dissipative structures maintained far from thermodynamic equilibrium, respond to this energy perturbation according to principles rooted in non-equilibrium thermodynamics. I propose an "Ecological Thermodynamic Fluctuation-Phase Transition" framework that treats the intensity of warming-driven energy fluctuations as the governing control variable determining ecosystem response modalities. The framework advances three core propositions: first, enhanced energy fluctuations compress the attractor basin of the current steady state within an energy landscape, systematically reducing ecological resilience before any visible state change; second, when fluctuation intensity exceeds a critical threshold, the system is driven toward a self-organized critical state wherein any tiny perturbation can trigger cross-basin transitions, manifesting as ecological phase transitions; third, the direction of phase transition is guided by the maximum entropy production principle, with systems tending toward states characterized by faster energy dissipation, more rapid turnover, and structurally simplified configurations with higher entropy production rates. This framework is supported by metabolic scaling theory, statistical physics of critical phenomena, and thermodynamic extremal principles, and is realized through two novel indices: the Energy Sensitivity Index and the Phase Transition Warning Index. The theory provides a first-principles basis for unifying apparently disparate ecological responses to warming and offers a pathway toward predictive ecology grounded in energy and thermodynamics.

There have been many advancements in the field of aerospace and avionics. Scientists have increasingly started to focus on VTOL (vertical take -off and landing) aircrafts. We have built a miniature VTOL twinrotor UAV. UAVs have begun to grab a lot of attention these days due to its numerous applications such as surveillance and relief. Twinrotor is a kind of a helicopter having two main propellers instead of one and no tail fin. All three important motion of the aircraft i.e. roll, pitch, yaw are controlled by thrust vectoring using servo motors and changing the magnitude of thrust using electronics speed controllers. The paper deals with the design of a basic UAV based on application and the construction keeping in mind the different concepts that govern its motion.

The virtual reality scene generation is a state of art, real time computer image generated to visualize geographically expansive and detailed virtual world on personal computers. Provide real time single or multiple channel visualization of virtual environments, dynamic moving models, and special effects using Microsoft direct X standards. In this project, we present car parking project with a 3D complex virtual reality environment. For our project, we created a car parking simulation. This car parking will be similar to the virtual application at road or parking lot. We created a road environment complete with people, appropriate background. Through a set simulation, created a situation allowing trained new driver personnel to experience and learn from car parking simulations.

Maintaining the air pressure of a closed, compressor-fed tank within a narrow band is a common requirement in pneumatic systems. This paper presents the design, implementation, and experimental evaluation of a proportional-integral-derivative (PID) controller for regulating the pressure of such a tank using a low-cost Arduino platform, an MPX5700AP pressure transducer, and a servo-actuated quarter-inch valve. The plant was first characterised by an open-loop step test, which yielded a first-order-plus-dead-time model with dead time L = 0.30 s and time constant T = 9.94 s. Initial controller gains were obtained from the Ziegler-Nichols reactioncurve rule and then refined experimentally to optimise the closed-loop response. The final controller produced a stable, monotone response with no overshoot, a rise time of 9.25 s, a settling time of 9.98 s, and a steady-state error of only 0.01 bar, and it returned the pressure to the set point after load disturbances without lasting offset. The results show that an inexpensive, microcontroller-based PID loop can deliver accurate and robust closed-tank pressure regulation, making the design suitable for laboratory, prototyping, and teaching applications.

The Ziegler-Nichols (ZN) reaction-curve rule remains the default starting point for tuning proportional-integralderivative (PID) controllers, yet its underlying assumption of a linear, self-regulating first-order-plus-dead-time (FOPDT) plant is frequently violated by low-cost pneumatic hardware. This paper reports a fully instrumented case study of closed-tank air-pressure regulation built around an Arduino Uno, an MPX5700AP pressure transducer, and a servo-actuated quarter-inch ball valve. Open-loop step testing identified an apparently benign, lag-dominant process (dead time L = 0.30 s, time constant T = 9.94 s, L/T = 0.030). Despite this favourable ratio, the ZN-derived PID controller produced a 66 % overshoot (peak 2.63 bar against a 1.58 bar set point) and a sluggish, oscillatory recovery. We attribute the failure to two coupled effects that ZN ignores: the strongly asymmetric, supply-saturated actuator authority of a single-acting pneumatic plant, and the resulting integral windup during the slow pressurisation transient. A structured, two-stage empirical refinement that raised the proportional gain roughly 150-fold while reducing the integral weight to one-quarter and the derivative weight to about one-seventh of their ZN values converged to a high-gain, near-proportional regulator. The refined controller eliminated overshoot entirely, settled in 9.98 s, held a steady-state error of 0.01 bar, and rejected manually injected load-valve disturbances without offset. The gain trajectory is shown to be functionally equivalent to a manual anti-windup detuning, providing a transparent, reproducible teaching example of whenand why-classical tuning must be abandoned for saturating pressure loops.

Understanding predator-prey dynamics is essential for maintaining ecological balance and biodiversity. Classical models often fail to capture complex biological behaviors such as prey defense mechanisms and nonlinear predation effects, which are vital for accurately describing real ecosystems. In light of this, there is a growing need to incorporate behavioral and functional complexity into mathematical models to better understand species interactions and their long-term ecological outcomes. This study aims to develop and analyze a predator-prey model that integrates two key ecological features: a Holling type III functional response and the anti-predator behavior exhibited by prey. The model assumes a habitat with limited carrying capacity to reflect environmental constraints. We formulate a nonlinear system of differential equations representing the interaction between prey and predator populations. The model is examined analytically by identifying equilibrium points and analyzing their local stability using the Routh-Hurwitz criteria. A literature-based theoretical analysis is supplemented with numerical simulations to validate and illustrate population dynamics. The model exhibits three equilibrium points: a trivial solution (extinction), a predator-free equilibrium, and a non-trivial saddle point representing coexistence. The non-trivial equilibrium best reflects ecological reality, indicating stable coexistence where prey consumption is balanced by reproduction, and predator mortality aligns with energy intake. Numerical simulations show that prey populations initially grow rapidly, then decline as they reach carrying capacity, while predator populations grow after a time lag and eventually stabilize. The results are further supported by the eigenvalue analysis, confirming local asymptotic stability. The proposed model realistically captures predator-prey dynamics, demonstrating that the inclusion of anti-predator behavior and a Holling type III response significantly affects population trajectories and system stability. This framework provides a more ecologically valid approach for studying long-term species coexistence and highlights the importance of incorporating behavioral responses in ecological modeling.

This paper introduces a cost-effective control method to enhance the low voltage ride-through (LVRT) capability and smooth the output power of a three-phase multilevel flying capacitor inverter (FCI) in wind turbine-based permanent mag net synchronous generator (PMSG). The proposed approach utilizes the energy storage capability of flying capacitors to mitigate wind power fluctuations and address short-duration outages and deep voltage sags. Additionally, a nonlinear controller based Lyapunov theory is developed to regulate capacitor voltages, improve power factors, and balance DC-link voltage. Numerical simulations are conducted in MATLAB/SimPower systems environment to validate the effectiveness of this comprehensive control strategy across different grid operation scenarios.

For decades, archeological site exploration has presented major challenges due to narrow spaces, unstable structures, and the high sensitivity of historical artifacts. Recent advancements in robotic technologies have introduced highly capable and reliable alternatives for safe and efficient exploration in environments that are otherwise inaccessible or hazardous to humans. This paper presents mathematical modeling, design, control and implementation of a bio-inspired autonomous snake robot tailored for the exploration of confined environments, with a particular focus on archeological sites. Our primary contribution is a novel system integration approach designed specifically for highly confined and fragile heritage environments, successfully combining a modular alternating-joint architecture with a ROS-based control framework and an AI-driven perception system focused strictly on YOLOv11-based artifact and obstacle identification. A physical network model was developed using MAT-LAB Simscape to simulate the system dynamic behavior under varying payloads. The control architecture was implemented using the robot operating system (ROS), supporting real-time execution of multiple locomotion strategies through coordinated servo actuation. The system is validated through simulation and physical experiments, demonstrating stable undulatory locomotion, accurate mapping in confined environments, and reliable artifact detection under variable lighting and occlusion. The results indicate that snake-inspired robotic platforms provide a viable and scalable solution for autonomous exploration and documentation in sensitive heritage sites.

The paper will present one specific aspect of the PhD research called Cibersemiótica e Processos de Projeto: Metodologia em Revisão, funded by FAPESP, which in turn is linked to the Nomads.usp research group of the University of São Paulo. The paper discusses the relevance of communication and information management in the digital design processes from the synchronic study of concepts such as feedback loop, control and self-regulation. These concepts are present in both biosemiotic and interactive design of functional cycle proposed in 1934 by biologist Jakob von Uexküll, as in cybernetic development proposed by Gordon Pask in his sophisticated Conversation Theory in the early 1970's.

This work introduces a unified theoretical framework integrating cosmology, quantum physics, complex adaptive systems, informational organization, collective dynamics, and memory-constrained observability within a single structurally coherent architecture.

The framework establishes a direct integration between:

the Unified Cosmology–Quantum Framework (UCQ),
the DUAL system,
Crowd-Based Dynamics (CBD),
and memory-dependent observability models.

Rather than proposing a purely reductionist unification of existing theories, the framework introduces a higher-level structural configuration space in which geometry, quantum states, information, memory, and projection dynamics coexist within a unified formal system.

The global state of the system is defined as:

Ω(t)=(G(t),Q(t),I(t),M(t))

where:

G(t) represents gravitational geometry,
Q(t) quantum dynamical states,
I(t) informational organization,
M(t) memory-dependent structural persistence.

The framework introduces unified operators governing:

structural evolution,
projection and observability,
informational accumulation,
saturation dynamics,
stability and instability regimes,
irreversibility and hysteresis,
conditional reversibility,
governability limits in complex systems.

A central contribution of the work is the integration of memory as a fundamental non-Markovian operator capable of generating persistence, delayed effects, path dependence, and structural transformations across multiple domains.

The framework establishes formal correspondences between:

quantum observability,
cosmological configuration spaces,
collective psychodynamics,
nonlinear complex systems,
and informational stability dynamics.

The proposed architecture remains mathematically coherent, structurally closed, computationally extensible, and experimentally testable through numerical simulations, projection dynamics, and cross-domain validation protocols, including links with double-slit observability regimes and collective saturation dynamics.

This corpus aims to provide a unified scientific architecture capable of connecting physical, informational, cognitive, and collective phenomena within a common structural language.

It has been studied that fear plays a significant role in establishing ecological communities, influencing biodiversity, and preserving ecological balance in predator-prey interactions. In this study, it is proposed a discrete-time predator-prey model that takes the fear effect into account that is derived by using Euler method. Objective of this study is analyzing the model by linearization. Similar to the continuous model properties, the trivial fixed point and the predator-free fixed point are both unstable. The discrete model differs from the continuous model in that the stability of the interior fixed point and the free prey fixed point is affected by the time step size. Using numerical methods, we examine period-doubling bifurcations related to interior fixed point and prey-free point that are impacted by time step size.

Electro-hydraulic servo systems utilizing multi-stage hydraulic cylinders (MSHCs) in erection mechanisms face strong nonlinearities, time-varying loads, and model uncertainties that challenge conventional controllers. This paper develops and compares different control strategies for such systems: the classical Proportional-Integral-Derivative controller (PID), a PID controller whose gains are tuned via Particle Swarm Optimization (PSO), fractional order PID tuned by PSO (FOPID-PSO), and a robust Sliding Mode Control (SMC) scheme with Lyapunov-based design and a boundary-layer implementation to mitigate chattering. A nonlinear model of the erection mechanism and MSHC, including inter-stage impacts captured by a Kelvin-Voigt impact model and controlled by a proportional directional control valve, is formulated and simulated using MAT-LAB/Simulink. Results show that PSO-optimized PID significantly improves tracking and settling behavior over baseline PID, FOPID-PSO adds flexibility to the PID, while robust SMC maintains accuracy and disturbance rejection under large load variations, but with a pronounced peak control signal during the stage-transition interval. The study quantifies performance, demonstrating that the control approaches enhance stability and robustness, with SMC offering the strongest resilience to uncertainties and PSO providing a simple and high-performance tuning route for implementation. The results are based on numerical simulation and serve as a baseline for future experimental validation and hardware realization.

This paper presents the control system development of the Rutgers Ankle rehabilitation device. The “Rutgers Ankle” is a haptic interface with a Stewart platform structure driven by six double-acting pneumatic actuators. Each cylinder input is controlled by one set of on/off solenoid valves. For overall system control, an interrupt handler loop is designed based on hardware interrupts. For precise flow rate control of the solenoid valves, a PWM scheme is proposed for a set of two on/off valves. The proposed PWM logic compensates the dead band of the valve response time. A distribution method for the desired pressure differential of the two air chambers of an actuator is proposed. The method is based on the minimization of the difference between the desired and measured pressure. During experiments, one actuator achieved a rise time of 90 ms and 0.3 mm resolution in an independent position control loop. The Rutgers Ankle has a 7 Hz mechanical bandwidth and allows stiffness control for...

„The more scientifically educated a person is, the longer he has attended school, the greater are the barriers he has to overcome on the way to holistic thinking“.

Hans Ulrich / Gilbert Probst

As in many other areas, it is well known that a fundamentally different way of thinking is required for management. It is usually given the terms "holistic", "systemic" or "networked".

Unmanned Ground Vehicle with Firing Mechanism" which has an unprecedented success in military navigation and combat tactics. The movement of military vehicles is always risky. We have created an ingenious remotely operated design that combines remote driving and firing mechanisms to launch projectiles in a variety of difficult conditions. The remotely controlled vehicle may process up to 4 driving modes, including forward/backward, left/right driving, and rotation-based shooting system for military operation, thanks to an intelligent control system and inventive tires. It has a killer LED light and a slider for the firing weapon, giving you a fantastic visual experience. This type is completely different from the type of civilian vehicles. When building military vehicles, uneven roads, dangerous environments, barriers to the use of GPS, war conditions, etc. are taken into consideration. A variety of electrical and mechanical components have been compiled to make the prototype. It is powered by four gear motors (12V). 12V DC battery is used for supply electrical power. Three servomotors control a dummy AK-47 weapon. Omron 5A Cube Relay consists of an electromagnet that transforms an electrical signal to mechanical motion and a switch that opens and shuts the electric circuit. The "Arduino Uno" module (5V) is an open source microcontroller which converts analog signals to digital signals. There are three "ESP 32" cameras that have been used for observing the movement of the vehicle, targeting aim and artificial intelligence (AI). Driver's instructions are provided via "HC 05" Bluetooth module. The average speed is 0.77 m / s and the braking distance is 13 cm to 16 cm. Its arms can rotate 115°along the horizontally and 100° vertically. The probability of hitting the target is 45% which is a bit less. After the first round of shots was fired, aim becomes slightly deviated due to the counter-thrust of the weapon. Moreover, the performance of the built prototype is as expected and satisfactory.

This paper presents a receding horizon genetic algorithm (RHGA) for dynamic resource allocation. The algorithm combines methods from control theory and computational intelligence to simultaneously solve the problems of (i) coordinated control of resources, (ii) task assignment, and (iii) multiple target tracking in a dynamic environment. A simulated case study on optimal positioning of a fleet of tugs along the northern Norwegian coast serves as a means of evaluating the algorithm. In terms of reducing the risk of oil tanker drifting accidents, the study shows that the RHGA is able to iteratively plan movement trajectories for each individual tug such that the net collective behaviour of the tugs outperforms that of stand-by tugs stationed at bases located uniformly along the coast. The promising results suggest great potential for further development and generalisation to other dynamic resource allocation problems.

(SINDy) a tres sistemas experimentales: el circuito de Chua, el circuito Jerk y un péndulo simple. Los datos de medición se obtuvieron a partir de el armado experimental de los sistemas físicos y se procesaron con filtrado de Savitzky-Golay. Se construyeron bibliotecas de características con restricciones físicas para cada sistema, y las ecuaciones identificadas se validan comparando trayectorias simuladas con los datos medidos mediante las métricas RM SE y R 2 .

We study a quantum-runtime hypothesis that is narrower than“betterqubits”and broader
than ordinary hardware-aware compilation: distinct subroutines of a quantum program may
require different protection profiles and different qubit-array geometries because they carry
different kinds of informational fragility. The runtime considered here classifies circuit
windows into phase-sensitive, globally entangled, arithmetic, weak-signal, magic-state, and
stabilizer-oriented workloads, and then allocates both protection and geometry accordingly.
We evaluate this idea in simulation using hardware-informed calibration inputs,
structured logical noise, explicit geometry profiles, and paired condition randomness so that
ablation modes face the same seeded noise realization. The focused three-regime study uses
96 replicates across three superconducting backends and compares four runtime modes:
uniform, protection-only, geometry-only, and protection-plus-geometry, each under static
and workload-reactive noise. Geometry is not a universal accelerator. Instead, it behaves
as a selective coherence-control variable. In the paired geometry-on-top-of-protection
comparison, the strongest gains occur for global parity and weak-signal spectroscopy under
mixed workload-reactive noise, with mean useful-output improvements of approximately
+0.188 and +0.181, respectively. A stabilizer-specific geometry refinement converts an earlier
regression into a helpful-clean result in the same regime.

SEPIC is a DC-DC converter that operates in both boost and buck modes, thereby reducing voltage stress on the active power switches. It is utilized in electric vehicles, marine vessels, and aircraft to minimize dimensions, mass, maintenance, and operational expenses while enhancing efficiency, safety, and dependability. DC microgrids, characterized by their straightforward topology and economical materials, provide enhanced efficiency relative to AC microgrids. This work reviews the previous literature concerning SEPIC converters and DC-DC microgrid applications. This paper presents a SEPICbased DC-DC converter designed for direct connection to a unipolar 120V DC microgrid and capable of delivering 600W of DC power. It is outfitted with a current sensor and a protective switch to provide self-protection against microgrid disturbances, such as brief short circuits. The converter has been designed and evaluated using PSpice. The simulation results indicated that during a sudden disturbance in the DC microgrid, the current sensor detected an excessive current, prompting the control circuit to deactivate the protective switch. This action isolated the input voltage from the converter circuit, leading to an immediate reduction of the input current to zero and a subsequent decline of the output voltage toward zero. The condition endured for approximately 50 milliseconds, anticipating a possible recovery from the disruption. Therefore, the simulation results confirmed the design methods of the proposed converter and demonstrated adequate protection against high current events.

This paper discusses the process of modelling and parameter selection for the creation of the electronic wedge brake system (EWB). The system involves a permanent magnet DC engine (PMDC) that drives the motor, the gear leadscrew, and the brake core. The proposed model is simpler and more flexible which can be used in both the most well-known EWB designs either natural or optimized EWB. The selection of the motor is rendered according to the brake specifications. The wedge angle profile is centred on the derivation of EWB system that consists of brake actuator, wedge mechanism dynamic, and wedge characteristic brake factor. Control and optimization are carried out with specific coefficients of friction of the brake pads to maintain operating reliability. A 5th-order brake simulation model of the EWB in a single state-space was derived and a simulation was conducted to verify the distribution of force. The efficiency of the brake clamping force control system was assessed by proportional-integral-derivative (PID) control. The performance of the proposed controller is verified in simulations and experiments using a prototype electronic wedge brake. The research findings indicate, the actuator restriction is deemed to achieve consistent performance against full range braking during the EWB control design.

The paraxial wave equation, a simplified version of the full electromagnetic wave formulation, is frequently employed to characterize optical signal transmission in these materials, facilitating an efficient and precise description of light propagation. This study examines the dynamical characteristics of the proposed model using both analytical and dynamical methods, specifically employing a bifurcation approach. Initially, wave transformation is applied to convert the proposed model into its conventional form. The system's dynamic properties are then examined using phase and Hamiltonian portraits, considering different parameter settings. We also find bright periodic, kink, bright-type, and dark-type bell wave, anti-kink, and solitary wave solutions by changing parameters, using their corresponding Hamiltonians, and integrating heteroclinic and homoclinic orbits. We also visually represent various characteristics by carefully choosing the right parameters. Moreover, the physical characteristics and computational results support the robustness and significance of the proposed theory.

The Conjugate Photonic Model (CPM) describes the photon as a rotating spherical dipole in the linear regime, travelling at. This paper demonstrates that such description is entirely coherent with Maxwell's equations: the electric and magnetic field functions derived from the spherical dipole geometry reproduce exactly Maxwell's plane-wave solutions when the system reaches and undergoes total Lorentz contraction (). It is further demonstrated that the wavelength is not the simultaneous spatial extent of the photon, but the linear distance travelled by the photonic disc in exactly one complete rotation of the dipole:. The photon is not distributed over the entire at a given instant-it is localised in a single phase plane that traverses over one period. The sine and cosine functions of Maxwell's waves describe the accumulated phase along the path, not the simultaneous position of the field. The dipole field functions are derived explicitly and shown to be consistent with , , and for macroscopic observers.

E cient control algorithms are developed to implement sti virtual walls without chatter. An analysis of the complete coupled system comprising controller, interface device, and user's nger underlies the design of a wall algorithm, thus each virtual wall is tailored to a speci c user impedance. The nger is modeled as a static second order impedance with justi cation drawn from empirical studies of limb dynamics available in the literature and from observations of the disparity in time scales between contact instability and volitional control. Compensation is incorporated for the destabilizing e ects of the zero order hold using either model based prediction or design in the digital domain. The destabilizing e ects of asynchronous wall on o switching times and sampling times are tracked by a special watchdog while deadbeat control is used to periodically eliminate these effects. Extensions are discussed, including on-the-y system identi cation of the user impedance.

Manual control performance on-board a moving vehicle is often impeded by biodynamic feedthrough-the effects of vehicle motion feeding through the operator's body to produce unintended forces on the control interface. In this paper, we propose and experimentally test a model-based controller that acts through a motorized manual interface to cancel the effects of biodynamic feedthrough. The cancellation controller is based on characterization data collected using an accelerometer on the vehicle and a force sensor embedded in the manual interface and a protocol under which the manual interface is temporarily immobilized while in the grip of the operator. The biodynamic model fit to the data is based in turn on a carefully constructed model of the coupled vehicle-operator system. The impact of biodynamic feedthrough and the ability of the model-based controller to cancel its effects were estimated through an experiment in which 12 human subjects used a joystick to carry out a pursuit tracking task on-board a single-axis motion platform. Cancellation controllers derived from biodynamic models fit individually to each subject significantly improved pursuit tracking performance, as evidenced by a 27% reduction in root-meansquare tracking error, a 35% improvement in time-on-target, and an increase in crossover frequency from 0.1 to 0.14 Hz.

This work represents a systematic computational study of the distribution of the Fourier coefficients of cuspidal Hecke eigenforms of level $\Gamma_0(4)$ and half-integral weights. Based on substantial calculations, the question is raised whether the distribution of normalised Fourier coefficients with bounded indices can be approximated by a generalised Gaussian distribution. Moreover, it is argued that the apparent symmetry around zero of the data lends strong evidence to the Bruinier-Kohnen Conjecture on the equidistribution of signs and even suggests the strengthening that signs and absolute values are distributed independently.

Résumé -Le confort est une notion globale: chaleur et froid, lumière, bruit, paysage, eau, verdure, prestige…. et autre, sont autant d'éléments définissant plusieurs paramètres climatiques, esthétiques, psychologiques du confort. Le confort est également la sensation subjective qui n'existe pas en lui-même. Ce n'est que par l'inconfort qu'on peut l'apprécier. Cette appréciation est différente selon la société et pour une même société suivant les individus. Des chercheurs commencent à défier l'hypothèse d'universalité, et à discuter que le fait de ne pas prendre en compte les dimensions culturelles, sociales, économiques et climatiques dans l'évaluation du confort, conduit à une exagération dans la définition des besoins pour le chauffage et la climatisation, c'est grâce à l'application universelle des outils d'évaluation du confort thermique qu'un inconfort thermique important est perçu par les sujets considérés. De ce fait, il n&#...

The study presents a comparative analysis of two advanced high-order sliding mode control (HOSMC) strategies-super-twisting sliding mode control (STSMC) and third-order sliding mode control (TOSMC)-for enhancing the performance of doubly-fed induction generator (DFIG)-based wind energy conversion systems (WECS). The key goals are to maximize energy efficiency, minimize the total harmonic distortion (THD) in the stator current, and reduce electrical losses within the system. Both control strategies are integrated into a direct field-oriented control (DFOC) scheme using space vector modulation (SVM) to improve dynamic response and control accuracy. MATLAB/Simulink simulations show that TOSMC consistently outperforms STSMC in multiple performance aspects. TOSMC ensures better energy efficiency through precise tracking of active and reactive power references while mitigating transient oscillations (chattering effects). Furthermore, TOSMC significantly reduces harmonic distortion, achieving a THD of 0.21%, compared to 0.33% for STSMC, and surpasses conventional controllers, which exhibit a minimum recorded THD of approximately 0.46%. The mitigation of transient phenomena also contributes to reduced switching losses and ohmic heating, thereby enhancing the generator's thermal stability and overall reliability.

In the present paper we have discussed concerning Godel’s incompleteness theorem(s) and plausible implications to artificial intelligence/life and human mind. Perhaps we should agree with Sullins III, that the value of this finding is not to discourage certain types of research in AL, but rather to help move us in a direction where we can more clearly define the results of that research. Godel’s incompleteness theorems have their own limitations, but so do Artificial Life (AL)/AI systems. Based on our experiences so far, human mind has incredible abilities to interact with other part of human body including heart, which makes it so difficult to simulate in AI/AL. However, it remains an open question to predict whether the future of AI including robotics science can bring this gap closer or not. In this regard, fuzzy logic and its generalization –neutrosophic logic- offer a way to improve significantly AI/AL research.[15]

This work aims to control the DFIG-based wind turbine conversion system by proposing an advanced control scheme for both the rotor-side and grid-side power converters to control power flow, maintain DC-link voltage stability, and enhance current quality. The proposed approach combines PI control with a modified super-twisting controller based on a smooth tangent hyperbolic. A PID-type sliding surface is introduced to improve robustness while further reducing chattering effects. The reference active power is generated by a mechanical control system using a PI controller applied to the turbine rotational speed. The stability of the system is analytically studied by using Lyapunov theory. To prove the effectiveness of the proposed control strategy, comparisons with other control techniques reported in the literature are carried out under various operating conditions. Simulation results obtained using MATLAB/Simulink confirm the improved performance and the effectiveness of the proposed approach.

Currently (2025), deep learning is the most important and popular methodology in artificial intelligence (AI) and artificial neural network (ANN) is the foundation of deep learning. The main drawback of ANN is the boom problem of a huge number of parametric weights when ANN in deep learning establishes a large number of hidden layers. The boom problem can be alleviated by high-performance computer but will be serious in case of high-dimension input data like image. The excellent solution for image processing within context of deep learning is that large parametric weight vector is reduced into much smaller window encoded by a so-called filtering kernel which is often 3x3 matrix or 5x5 matrix which is convoluted over entire image data. ANN with support of such filtering kernel is called convolutional neural network (CNN). Many researches prove that CNN is feasible and effective in image processing. The hidden cause of the effectiveness of CNN is that the visionary structure of an image is aggregated in such a way that filtering kernel is ideal to extract image features. However, it is not asserted that matrix-based filtering kernel is appropriate to other high-dimension data that is not image. Another solution of the boom problem is that large parametric weight vector is organized as matrix that is the same structure of 2-dimension data like image, which leads to a so-called matrix neural network (MNN) whose parameters are weighted matrices. Computation cost of MNN is decreased significantly in comparison with ANN but it is necessary to test the effectiveness of MNN with respect to CNN. This is the main hypothesis “whether MNN is the alternative of CNN” which is tested in this research, hinted by the research title. Moreover, transformer which is the new trend (2025) in AI and deep learning, which aims to improve/replace traditional ANN by self-supervised learning, in which attention is the significant mechanism of self-supervised learning. Anyhow, attention which is the cornerstone of transformer is the representation of internal structure/relationship inside high-dimension data like image. Therefore, the implicit deep meanings of attention and filtering kernel are similar, which represents feature of data, which does not go beyond parametric weights too. In general, the research has two goals: 1) explaining and implementing ANN, CNN, and transformer (attention) and 2) applying analysis of variance (ANOVA) into evaluating the effectiveness of ANN, CNN, and transformer (attention) within context of image classification. The ultimate result is that it is not asserted that MNN is the alternative of CNN but MNN can be an optional choice for implementing ANN in context of image processing instead of focusing on the unique CNN solution. Moreover, the incorporation of MNN and attention in implementing transformer produces a compromising solution of high performance and computational cost.

Naturalistic observations of infant/caregiver social attention have yielded rich information about human social development. However, observational data are expensive, laborious, and reliant on fallible human coders. We model interactions between caregivers and infants using a three dimensional simulation environment in order to gain greater insight into the development of infant attention sharing, specifically gaze following. Most models of infant cognition have been only abstractly linked to the detail of a real life environment and ...

In recent times, the design of controllers for ‘self-driving’ vehicles has received significant attention from a number of researchers. A significant move in this context is a law passed in states such as California, that allows the testing of self-driving cars on its roads. In light of such developments, safety of the passengers in such vehicles along with
demands on their performance are major concerns. Quite naturally, these vehicles are required to satisfy a number of requirements irrespective of the road conditions (say, snow, potholes etc.), varying number of passengers, collisions with other vehicles, and so on. Adding to these challenges is the fact that any vehicle’s driving or braking force, and
rate of steering are limited due to physical constraints. Moreover, excessive activation of these limits could cause problems such as loss of vehicle stability (for example, excessive braking on slippery roads causes the wheels to slip, and a subsequent loss of vehicle control). In this report, we present the design and performance analysis of an adaptive
control scheme that achieves stabilization of a vehicle’s speed and orientation, despite unknown model parameters, input constraints, and the presence of unwanted external disturbances. The vehicle model considered is the so called bicycle model, in which the mass, length, and coefficient of viscous damping are regarded as unknowns. This is motivated by the following reasons:
• The vehicle’s mass could change as the number of passengers could be different on each trip.
• The length of the vehicle is considered as unknown, despite being easily measurable, as a car manufacturer
would like to use the same controller across a variety of vehicle platforms.
• The coefficient of viscous damping could vary due to different road and atmospheric conditions.
The design of the controller follows the ‘command generator tracker’ approach (see [1]), which is suitable for a
multi-input multi-output (MIMO) system, such as ours. To design the controller, we assume that the plant is linear,
and follow the steps described in [1]. Next, an error governor (see [2]) is introduced in order to moderate the controller
and satisfy the input constraints. Finally, using simulations, the obtained controller is tested on the nonlinear plant.
The obtained results prove the efficacy of the control design.
The rest of this report is organized in the following manner: The problem is described, and the team’s original
contributions made while solving it are stated in Section 2. Section 3 describes the vehicle’s dynamic model, and Section 4 presents the design of the controller. Simulation results are depicted in Section 5. Finally, the conclusions are presented in Section 6. Attachments, which include our Matlab and Simulink code, are provided in the Appendix.

State Dependent Riccati Equation (SDRE) approach is a modification of the well studied LQR method. It has the capability of being applied to control nonlinear systems. In this paper the technique has been applied to control the single inverted pendulum (SIP) which represents a rich class of nonlinear underactuated systems. SIP modeling is based on Euler-Lagrange equations. A procedure is developed for judicious selection of weighting parameters and constraint handling. The controller designed by SDRE technique here gives better results than existing controllers designed by energy based techniques.

The concept of superquadratic functions of several variables with general kernels in the setting of time scales play a fundamental role in mathematical analysis. In this article, we derive some new results related to Hardy-type inequalities through Jensen inequality for multivariate superquadratic functions on time scales.

Pedagogical landscapes are quickly changing worldwide due to the use of digital technology in the delivery of educational instructions. Digital technology has enormous potential for change in our Nigerian educational system which continues to struggle with issues including overcrowding in classrooms, a lack of resources for instruction, and teacher shortage. This paper discourse analyzes how artificial intelligence (AI) could inspire educational innovation with an emphasis on research writing and tailored learning. This contextual literature-based study critically examines the multifaceted implications of Adaptive Learning Algorithms, Intelligent Tutoring System (ITS), Learning Analytics/Predictive Modeling, Natural Language Processing (NLP), Recommendation Systems, Automated Assessment/Personalized Feedback, and Behavioral/Cognitive Modeling tools that can be used to improve students' academic writing skills, customize instruction, and enable self-paced learning. These include improved access to quality instruction, personalized and student-centered learning, enhanced teacher effectiveness, and the bridging of urban-rural educational divides. However, the paper also identifies a number of contextual obstacles that hinder the successful integration of AI in Nigerian schools and universities and thus suggested that government and other parties involved in education should prioritize them, including collaborations, infrastructure investment, established AI laboratories, digital innovation centers, and smart classrooms.

This paper explores the use of kinship terminologies in English and Urdu by attempting a comparative-lexical analysis using Morgan's (1871) classification of kin into consanguineal and affinal relatives. In other words, the conceptual framework of the paper is based on Morgan's (1871) notion of the patterns of kinship system while the methodological framework is comparative-lexical. The sample consists of three media texts including a drama and a film from English and a drama from Urdu. It was found that kinship works in the same way in both the languages that follow different patterns of kinship: English is Dravidian while Urdu is Sundanese. It is suggested that this is because of the difference in the notions of family unit (nuclear/ joint) and their approach to life, individual and/ or community-based. The paper is intended to deepen understanding of the kinship terminologies in both languages in the absence of any earlier contrastive study of both the languages. It also intends to add meaningfully to the fields of Linguistics, Anthropology, and Sociology.

We formulate a concrete effective electrodynamic model that realizes the hypothesis that local lowfrequency electromagnetic oscillation and freely propagating electromagnetic radiation are distinct physical sectors. The construction is deliberately minimal: the longitudinal electrostatic sector is left unchanged, while the transverse dynamical sector is modified by a threshold frequency ωc. For monochromatic sources, the transverse field equation becomes a Helmholtz equation with effective wave number q(ω) = c-1 √ ω 2-ω 2 c. When ω > ωc, q is real and the solution contains an outgoing 1/r far-field term. When 0 < ω < ωc, q = iκ is imaginary and the transverse field is Yukawa-like, decaying as e-κr /r; hence the asymptotic radiative flux vanishes identically. Within this model, the existence of a minimum frequency for free radiation is therefore not postulated informally but derived explicitly from the field equation. We prove the vanishing of the radiativity functional below threshold, derive the modified dipole-radiation law above threshold, and show that quantization of the transverse sector yields a minimum free-photon energy Emin = ℏωc. The price is equally explicit: the model is an effective theory in a preferred frame, not a Lorentz-invariant completion of Maxwell theory. This makes the proposal mathematically sharp, physically interpretable, and experimentally falsifiable.

Energy efficiency, achieving the maximum productive output per unit of energy consumed, represents one of the most cost-effective, technically proven, and immediately deployable strategies available to the petroleum industry for simultaneously reducing operational costs, improving competitiveness, and lowering greenhouse gas emissions intensity. This article provides a comprehensive review of energy efficiency in petroleum operations, covering the principal efficiency opportunity areas, available technologies, performance metrics, measurement and benchmarking frameworks, and the role of digital optimisation and simulation tools in realising efficiency potential. The petroleum sector is one of the most energy-intensive industries globally, with refineries alone consuming energy equivalent to 6-10% of the crude oil they process, representing a significant efficiency improvement opportunity. OGCI member companies achieved a 24% reduction in upstream carbon intensity between 2017 and 2024, attributable in significant part to energy efficiency improvements alongside methane reduction and flaring reduction programmes. The principal efficiency opportunity areas, rotating equipment optimisation, heat exchange and integration, steam system management, flare gas recovery, combined heat and power (CHP), and advanced process control, are examined in terms of their energy savings potential (ranging from 8% for APC to 35% for CHP), payback periods, and implementation challenges. The article examines the application of environmental simulation tools, including Aspen HYSYS for process integration analysis and HOMER Pro for energy system optimisation, in identifying and quantifying efficiency opportunities, drawing on the framework of Lamidi (2024) and the empirical results of Kour et al. (2025), who demonstrated 13.78% energy savings through integrated simulation of gas sweetening and dehydration operations. The role of AI-driven optimisation, real-time monitoring, and digital twin platforms in closing the gap between identified and realised efficiency potential is also discussed. Key findings confirm that a typical petroleum facility has unrealised energy efficiency potential of 15-30% of current consumption, achievable through a combination of operational improvements and capital investments with payback periods typically under 3 years.

This paper provides a close examination of specific intelligent tutoring system (ITS) architectures spanning the period 1988-1999. ITSs are classified into three categories, namely traditional three-model, classical four-model and new-generation architectures for the purposes of this study. Similarities and differences between architectures of the same category, and between different category architectures are discussed. The study depicts the influence of application domains, learning and instruction trends, as well as software development advances on ITS architecture and behaviour. This research aims to examine various ITS architectures and its actual behaviour to establish a set of generic characteristics and behaviour. These characteristics are useful for comparing and evaluating existing ITSs, and can guide the design of new ITSs.

Este artigo examina os fundamentos conceituais, a arquitetura técnica, as estratégias de aprendizagem e as implicações sociais da Inteligência Artificial Física (IA Física) ou IA Corporificada (Embodied AI). Ao contrário dos sistemas de IA tradicionais, que operam dentro das fronteiras dos ambientes digitais, a IA Física integra percepção, cognição e ação, para existir como agentes corporificados no mundo real. O artigo apresenta as tecnologias de sensores, arquiteturas de aprendizagem profunda, estratégias de treinamento de simulação para realidade e aprendizagem autossupervisionada multimodal como elementos-chave para a autonomia adaptativa. Aplicações práticas nas áreas de medicina, manufatura e segurança pública são apresentadas para ilustrar os avanços atuais. Por fim, o artigo discute os riscos econômicos, sociais e éticos associados à autonomia de tomada de decisão em máquinas e robôs humanoides dotados de IA embarcada, argumentando que a adoção em larga escala da IA Física representa uma mudança social cujas consequências devem ser analisadas criticamente.

The development of suspension systems arises from the impact of vehicle vibrations caused by road irregularities on passengers. Among various suspension systems, semi-active suspension (SAS) is favored for its cost-effectiveness and power efficiency. Magnetorheological (MR) dampers are commonly used in SAS to enhance vibration control by adjusting the magnetic field. However, the traditional sliding mode control (SMC) method often causes chattering, which affects performance. This study proposes the application of a super-twisting sliding mode controller (STSMC) to improve vibration control in SAS and overcome the chattering problem. Simulations and experimental evaluations were conducted on a quarter-car test bench with different road excitations. The results show that the STSMC-based system outperforms the traditional controller in vibration suppression. Specifically, the suppression effect on the root mean square value of body acceleration on a sinusoidal road surface can reach up to 38.2%. Therefore, the STSMC controller demonstrates superior vibration control in SAS systems equipped with MR dampers, providing a valuable reference for future research on SAS vibration control.

From the entomological box to the ight of the butter y: re ections on the procedural dimension of the sign and classes of signs in semiotic analyses based on text J & R () F &( -ORCID 0000-0001-7021-3341 P ( B ,--ORCID 0000-0002-4573-5807 (pág 117 -pág 129) . Este trabalho se propõe a uma análise das classes de signos de Charles Sanders Peirce em sua dimensão processual e contrapõe-se às perspectivas que as concebem como categorias estáticas. Defende-se que os signos devem ser compreendidos e interpretados dentro de um contínuo semiótico, onde as classes de signos operam como instrumentos para mapear os trajetos pelos quais os signos realizam seus propósitos. Para explorar essa abordagem processual, além da revisão da literatura peirceana, este estudo focaliza o artigo On the Algebra of Logic, a contribution to the philosophy of notation (1885), no qual Peirce introduz a tricotomia ícone-índice-símbolo. Argumenta-se que o método semiótico empregado por Peirce na análise da notação algébrica evidencia uma proto-sistematização das classes de signos em sua dimensão dinâmica. Essa reinterpretação proporciona uma compreensão mais aprofundada do funcionamento do signo e das classes de signos e seus desdobramentos teóricos. Palavras-chave: Charles S. Peirce; semiotica; classes de signos; álgebra da lógica; .loso.a do processo. . Este trabajo se propone a analizar las clases de signos de Charles Sanders Peirce en su dimensión procesual y se contrapone a las perspectivas que las conciben como categorías estáticas. De.ende que los signos deben ser comprendidos e interpretados dentro de un contínuo semiótico, donde las clases de signos operan como instrumentos para trazar los caminos a través de los cuales los signos cumplen sus propósitos. Para explorar este enfoque procesual, además de una revisión de la literatura peirceana, este estudio se centra en el artículo On the Algebra of Logic, a contribution to the philosophy of notation (1885), donde Peirce introduce la tricotomía icono-índice-símbolo. Se argumenta que el método semiótico empleado por Peirce en el análisis de la notación algebraica

This paper presents modelling and control for planar flexible-joint 2-DOF, an underactuated system. Thus designing to obtain stability of actuated joints and underactuated is a challenge for a control system. In the conventional sliding mode control method, the sliding surface is normally expressed based on the integer-order differentiation of the state variables. In the study, fractional order sliding mode control (FOSMC) algorithm is given, and then the sliding surface is designed by the fractionalorder calculus,i.e, using fractional-order differentiation of the state variables. Thus, the fractional dimension accelerating the change rate of angle deviation is contained in the control output, which means that the control output of the FOSMC is sensitive to the change rate of angle deviation and provides a prompt control output for the system. From which, FOSMC based on Lyapunov theory and fractional calculus is proposed for the robot to achieve the global stability of two joints. The effectiveness and feasibility of the proposed method are demonstrated by MATLAB/SIMULINK simulation that the robot model considers parametric uncertainty and external disturbance.