Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System

Rozali, Sahazati Md.; Rahmat, M. F.; Husain, Abdul Rashid

doi:10.1155/2014/679435

Cited by 12 publications

(10 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…MSMC is known to help the system track a shaped square wave signal. The references trajectory and the value of external disturbance, 10500 N which was used in this study is similar to that of [18] and [19].…”

Section: Simulation Results and Comparisonsmentioning

confidence: 99%

Optimization of Modified Sliding Mode Control for an Electro-Hydraulic Actuator System with Mismatched Disturbance

Rahmat¹,

Othman²,

Rozali³

et al. 2018

EECSI

Self Cite

View full text Add to dashboard Cite

This paper presents a modified sliding mode controller (MSMC) for tracking purpose of electro-hydraulic actuator system with mismatched disturbance. The main contribution of this study is in attempting to find the optimal tuning of sliding surface parameters in the MSMC using a hybrid algorithm of particle swarm optimization (PSO) and gravitational search algorithms (GSA), in order to produce the best system performance and reduce the chattering effects. In this regard, Sum square error (SSE) has been used as the objective function of the hybrid algorithm. The performance was evaluated based on the tracking error identified between reference input and the system output. In addition, the efficiency of the designed controller was verified within a simulation environment under various values of external disturbances. Upon drawing a comparison of PSOGSA with PSO and GSA alone, it was learnt that the proposed controller MSMC, which had been integrated with PSOGSA was capable of performing more efficiently in trajectory control and was able to reduce the chattering effects of MSMC significantly compared to MSMC-PSO and MSMC-GSA, respectively when the highest external disturbance, 10500N being injected into the system's actuator.

show abstract

Section: Simulation Results and Comparisonsmentioning

confidence: 99%

Optimization of Modified Sliding Mode Control for an Electro-Hydraulic Actuator System with Mismatched Disturbance

Rahmat¹,

Othman²,

Rozali³

et al. 2018

EECSI

Self Cite

View full text Add to dashboard Cite

show abstract

“…Equation 18is substituted for Equations (12), (14), (15), and (16). Then, Equation 18can be expressed as…”

Section: Theoremmentioning

confidence: 99%

“…Based on an objective function, the PSO algorithm could find the optimal values of the design parameters (c 1 , c 2 , c 3 , k 1 , k 2 ). These parameters are fed to the adaptive law, described by Equation (16). Then, the estimatedF, resulting from the adaptive law, is given to the nonlinear controller, described by Equation (15).…”

Section: Parameter Valuementioning

confidence: 99%

“…The design of the backstepping controller was firstly established based on a conventional setting of design parameters; then, a PSO was invoked to find the optimal values of these design parameters. Rozali et al designed a backstepping controller for an electro-hydraulic actuator (EHA) system [16]. Two optimization techniques were employed-gravitational search algorithm (GSA) and particle swarm optimization (PSO) techniques-for optimizing the design parameters of a backstepping controller, so as to improve the performance of the EHA system controlled by a backstepping controller.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Development of a New Adaptive Backstepping Control Design for a Non-Strict and Under-Actuated System Based on a PSO Tuner

Humaidi

Hameed

2019

Information

View full text Add to dashboard Cite

In this work, a new adaptive block-backstepping control design algorithm was developed for an under-actuated model (represented by a ball–arc system) to enhance the transient and steady-state behaviors and to improve the robustness characteristics of the controlled system against parameter variation (load change and model uncertainty). For this system, the main mission of the proposed controller is to simultaneously hold the ball at the top of the arc and retain the cart at the required position. The stability of a controlled system based on the proposed adaptive controller was analyzed, and its globally asymptotic stability was proven based on the Lyapunov theorem. A comparative study of adaptive and non-adaptive block-backstepping controllers was conducted in relation to the transient, steady-state, and robustness characteristics. The effectiveness of the controller was verified via simulation within a MATLAB/SIMULINK environment. The simulated results show that the proposed adaptive control strategy could successfully stabilize the under-actuated ball–arc system, regardless of both the regulation problem and the tracking problem. This provides a better dynamic performance and a better load rejection capability, and it performs well in solving the uncertainty problem in the model parameter.

show abstract

“…In particular, PSO algorithms were applied successfully in many robotic applications [30][31][32][33][34]. Nevertheless, only a few research papers were devoted to solving the control problem of constrained robotic manipulators [35,36] using PSO. In competition with them were a few research papers proposing use of neurofuzzy controllers in order to solve the robust control problem for constrained robotic arms [37][38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Robust Impedance Control-based Lyapunov-Hamiltonian Approach for Constrained Robots

Mehdi

Boubaker

2015

Int. j. adv. robot. syst.

View full text Add to dashboard Cite

A new design of a robust impedance controller for constrained robotic manipulators is presented. The main objective is to stabilize asymptotically, in the task space, the robotic manipulator's end effectors into a desired position, via a desired contact force under model uncertainties and measurement noise. In this work, the proposed approach is enough straightforward for application without force and position control separation. Robust asymptotic stability in the approach is proved using a HamiltonianLyapunov approach. Besides this, a state/parameter observer and an acceleration estimator are proposed to handle the problems of force estimation, disturbance rejection and acceleration measurement. To ensure high performance, a Particle Swarm Optimization (PSO) algorithm is used finally as an efficient and fast method for the offline fine-tuning of the controller's parameters. In designing the PSO method, the Mean of Root Squared Error (MRSE) is considered as a cost function in the Cartesian space. Finally, the example of the ABB-IRB 140 industrial robot with 6DOFs is used to validate the performances of the proposed approach.

show abstract

Performance Comparison of Particle Swarm Optimization and Gravitational Search Algorithm to the Designed of Controller for Nonlinear System

Cited by 12 publications

References 25 publications

Optimization of Modified Sliding Mode Control for an Electro-Hydraulic Actuator System with Mismatched Disturbance

Optimization of Modified Sliding Mode Control for an Electro-Hydraulic Actuator System with Mismatched Disturbance

Development of a New Adaptive Backstepping Control Design for a Non-Strict and Under-Actuated System Based on a PSO Tuner

Robust Impedance Control-based Lyapunov-Hamiltonian Approach for Constrained Robots

Contact Info

Product

Resources

About