Design of Optimal Sliding Mode Control of Elbow Wearable Exoskeleton System Based on Whale Optimization Algorithm

Waheed, Zharaa A.; Humaidi, Amjad J.

doi:10.18280/jesa.550404

Cited by 12 publications

(8 citation statements)

References 39 publications

(46 reference statements)

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“…As future extension of this study, other control schemes can be used to control the pendulum system [15][16][17][18][19][20], or one can use modern optimization techniques to tune the design parameters of SC and SMC towards their improvement [21][22][23][24][25].…”

Section: Simulation Resultsmentioning

confidence: 99%

A Comparative Study of Synergetic and Sliding Mode Controllers for Pendulum Systems

Mutlak,

Humaidi

2023

JESA

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This study presents a performance comparison between a synergetic controller (SC) and a sliding mode controller (SMC) applied to a pendulum system. Initially, the mathematical model of the pendulum system is established. Subsequently, the design of both synergetic and sliding mode controls is elaborated, leading to the development of control laws for the proposed controllers. The effectiveness of the pendulum system controlled by SC and SMC has been validated through numerical simulations. These simulations revealed that the control signal exhibits chattering behaviour in the case of SMC, while this phenomenon is absent with the SC, demonstrating a distinct difference in performance between the two control systems.

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Section: Simulation Resultsmentioning

confidence: 99%

A Comparative Study of Synergetic and Sliding Mode Controllers for Pendulum Systems

Mutlak,

Humaidi

2023

JESA

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“…Furthermore, the ASC can effectively constrain the estimation errors of uncertain parameters within defined bound to avoid the drifting problem in estimation errors, which may lead to instability of the controlled system. This study can be extended by suggesting another control scheme in the literature and a comparison study can be made with proposed controllers for the electronic throttle valve system [29][30][31][32][33][34][35][36][37][38][39][40][41].…”

Section: Discussionmentioning

confidence: 99%

Adaptive synergetic control for electronic throttle valve system

Mutlak,

Humaidi

2024

IRASE

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This study has developed adaptive synergetic control (ASC) algorithm to control the angular position of moving plate in the electronic throttle valve (ETV) system. This control approach is inspired by synergetic control theory. The adaptive controller has addressed the problem of variation in systems parameters. The control design includes two elements: the control law and adaptive law. The adaptive law is developed based on Lyupunov stability analysis of the controlled system, and it is responsible for estimating the potential uncertainties in the system. The effectiveness of the proposed adaptive synergetic control has been verified by numerical simulation using MATLAB/Simulink. The results showed that the ASC algorithm could give good tracking performance in the presence of uncertainty perturbations. In addition, a comparison study has been made to compare the tracking performance of ASC and that based on conventional synergetic control (CSC) for the ETV system. The simulated results showed that the performance of ASC outperforms that based on CSC. Moreover, the results showed that the estimation errors between the actual and estimated uncertainties are bounded and there is no drift in the developed adaptive law of ASC.

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“…For future work, this study can be extended by including different optimization algorithms for the purpose of comparison with the PSO technique [18][19][20][21]. In addition, another extension of this study could be by using other embedded hardware designs such as Raspberry Pi or FPGA or by using LabVIEW programming software in order to implement the proposed controller in a real-time environment [22][23][24][25].…”

Section: Discussionmentioning

confidence: 99%

Design and Implementation of Adaptive Backstepping Control for Position Control of Propeller-Driven Pendulum System

Hamoudi¹,

Rasheed²

2023

JESA

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The performance of the classical and adaptive backstepping control schemes for the angular position control of a nonlinear Propeller-Driven Pendulum System (PDPS) is investigated in this paper. A Particle Swarm Optimization (PSO) algorithm has been utilized to tune the design parameters of the proposed controllers. Based on the Lyapunov stability analysis the classical and the Adaptive Back-Stepping Controllers have been constructed in order to prove the convergence of the system's error with time. The Adaptive Backstepping Controller (ABSC) is designed to compensate for the variation in the system's mass magnitude. In terms of system transient response, a comparison study of the effectiveness of both controllers has been presented in this work. The simulation results have been obtained based on the MATLAB software. In addition, a comparison study between the proposed controllers and other controllers has been listed to demonstrate the effectiveness of the proposed controller. The simulation results show that the PSO based classical Backstepping Controller (BSC) has a better performance in terms of reducing the settling time, the steady-state error, and the Root Mean Square Error (𝑅𝑀𝑆𝐸) value in comparison with the STSMC and SMC. In addition, the simulation results reveal that the PSO based ABSC has a better performance in terms of reducing the steady state error and the maximum overshoot in comparison with the PSO based BSC and ASTSMC.

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Design of Optimal Sliding Mode Control of Elbow Wearable Exoskeleton System Based on Whale Optimization Algorithm

Cited by 12 publications

References 39 publications

A Comparative Study of Synergetic and Sliding Mode Controllers for Pendulum Systems

A Comparative Study of Synergetic and Sliding Mode Controllers for Pendulum Systems

Adaptive synergetic control for electronic throttle valve system

Design and Implementation of Adaptive Backstepping Control for Position Control of Propeller-Driven Pendulum System

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