Parameter tuning of sliding mode controller using multi-objective particle swarm optimization in electro-hydraulic actuator system

Electro-Hydraulic Actuator (EHA) system is very popular and widely applied in the modern industry applications. This is because of its advantages on the high force to weight ratio, accurate positioning with fast motion and capability in generating large torque. Due to its increasing trends in modern...

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Main Author:	Chai, Mau Shern
Format:	Thesis
Language:	English English
Published:	2021
Subjects:	T Technology (General) TJ Mechanical engineering and machinery
Online Access:	http://eprints.utem.edu.my/id/eprint/25979/1/Parameter%20tuning%20of%20sliding%20mode%20controller%20using%20multi-objective%20particle%20swarm%20optimization%20in%20electro-hydraulic%20actuator%20system.pdf http://eprints.utem.edu.my/id/eprint/25979/2/Parameter%20tuning%20of%20sliding%20mode%20controller%20using%20multi-objective%20particle%20swarm%20optimization%20in%20electro-hydraulic%20actuator%20system.pdf
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spelling	my-utem-ep.259792022-09-29T12:30:50Z Parameter tuning of sliding mode controller using multi-objective particle swarm optimization in electro-hydraulic actuator system 2021 Chai, Mau Shern T Technology (General) TJ Mechanical engineering and machinery Electro-Hydraulic Actuator (EHA) system is very popular and widely applied in the modern industry applications. This is because of its advantages on the high force to weight ratio, accurate positioning with fast motion and capability in generating large torque. Due to its increasing trends in modern applications, the research to control the EHA system has attract the attentions of many researchers around the world. However, the nonlinear characteristics in the dynamics of the EHA system such as internal leakage have make it difficult to control and hard to produce an accurate output such as position, force, and speed that are required in different applications. Internal leakage existed in the servo valve can degrade the overall performance of the EHA system. Commonly, a control system either open-loop or closed-loop is the key to overcome the aforementioned issue, where researchers had proposed many types of control strategies across the years ranging from classical to advanced controller to control the nonlinear EHA system so that it can suit into different industry applications. In this research, Sliding Mode Controller (SMC) is designed and proposed for the positioning control of the established EHA system. To obtain the optimum performance of the EHA system, Multi-Objective Particle Swarm Optimization (MOPSO) is implemented to the SMC to achieve the highest position output performance with least overshoot and steady-state error. In order to verify the effectiveness of the proposed SMC with MOPSO strategy, comparison study has been implemented to Proportional Integral Derivative (PID) and SMC controllers with conventional Particle Swarm Optimization (PSO) technique. The simulation results show that the proposed control strategy is able to improve the overshoot percentage of the EHA system by 99.78% and 99.64% as compared to the PSO-PID controller and PSO-SMC respectively. Robustness tests show the proposed control strategy achieved least overshoot percentage in all simulation case studies including the mass, pressure and internal leakage variations. 2021 Thesis http://eprints.utem.edu.my/id/eprint/25979/ http://eprints.utem.edu.my/id/eprint/25979/1/Parameter%20tuning%20of%20sliding%20mode%20controller%20using%20multi-objective%20particle%20swarm%20optimization%20in%20electro-hydraulic%20actuator%20system.pdf text en public http://eprints.utem.edu.my/id/eprint/25979/2/Parameter%20tuning%20of%20sliding%20mode%20controller%20using%20multi-objective%20particle%20swarm%20optimization%20in%20electro-hydraulic%20actuator%20system.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=121057 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Electrical Engineering Ghazali, Rozaimi
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Ghazali, Rozaimi
topic	T Technology (General) TJ Mechanical engineering and machinery
spellingShingle	T Technology (General) TJ Mechanical engineering and machinery Chai, Mau Shern Parameter tuning of sliding mode controller using multi-objective particle swarm optimization in electro-hydraulic actuator system
description	Electro-Hydraulic Actuator (EHA) system is very popular and widely applied in the modern industry applications. This is because of its advantages on the high force to weight ratio, accurate positioning with fast motion and capability in generating large torque. Due to its increasing trends in modern applications, the research to control the EHA system has attract the attentions of many researchers around the world. However, the nonlinear characteristics in the dynamics of the EHA system such as internal leakage have make it difficult to control and hard to produce an accurate output such as position, force, and speed that are required in different applications. Internal leakage existed in the servo valve can degrade the overall performance of the EHA system. Commonly, a control system either open-loop or closed-loop is the key to overcome the aforementioned issue, where researchers had proposed many types of control strategies across the years ranging from classical to advanced controller to control the nonlinear EHA system so that it can suit into different industry applications. In this research, Sliding Mode Controller (SMC) is designed and proposed for the positioning control of the established EHA system. To obtain the optimum performance of the EHA system, Multi-Objective Particle Swarm Optimization (MOPSO) is implemented to the SMC to achieve the highest position output performance with least overshoot and steady-state error. In order to verify the effectiveness of the proposed SMC with MOPSO strategy, comparison study has been implemented to Proportional Integral Derivative (PID) and SMC controllers with conventional Particle Swarm Optimization (PSO) technique. The simulation results show that the proposed control strategy is able to improve the overshoot percentage of the EHA system by 99.78% and 99.64% as compared to the PSO-PID controller and PSO-SMC respectively. Robustness tests show the proposed control strategy achieved least overshoot percentage in all simulation case studies including the mass, pressure and internal leakage variations.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Chai, Mau Shern
author_facet	Chai, Mau Shern
author_sort	Chai, Mau Shern
title	Parameter tuning of sliding mode controller using multi-objective particle swarm optimization in electro-hydraulic actuator system
title_short	Parameter tuning of sliding mode controller using multi-objective particle swarm optimization in electro-hydraulic actuator system
title_full	Parameter tuning of sliding mode controller using multi-objective particle swarm optimization in electro-hydraulic actuator system
title_fullStr	Parameter tuning of sliding mode controller using multi-objective particle swarm optimization in electro-hydraulic actuator system
title_full_unstemmed	Parameter tuning of sliding mode controller using multi-objective particle swarm optimization in electro-hydraulic actuator system
title_sort	parameter tuning of sliding mode controller using multi-objective particle swarm optimization in electro-hydraulic actuator system
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Electrical Engineering
publishDate	2021
url	http://eprints.utem.edu.my/id/eprint/25979/1/Parameter%20tuning%20of%20sliding%20mode%20controller%20using%20multi-objective%20particle%20swarm%20optimization%20in%20electro-hydraulic%20actuator%20system.pdf http://eprints.utem.edu.my/id/eprint/25979/2/Parameter%20tuning%20of%20sliding%20mode%20controller%20using%20multi-objective%20particle%20swarm%20optimization%20in%20electro-hydraulic%20actuator%20system.pdf
_version_	1747834147234119680

Parameter tuning of sliding mode controller using multi-objective particle swarm optimization in electro-hydraulic actuator system

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