Classical and metaheuristic optimizations performance in an electro-hydraulic control system

Chong, Chee Soon and Ghazali, Rozaimi and Chong, Shin Horng and Ghani, Muhammad Fadli and Md. Sam, Yahaya and Has, Zulfatman (2022) Classical and metaheuristic optimizations performance in an electro-hydraulic control system. International Journal of Mechanical Engineering and Robotics Research, 11 (3). pp. 192-197. ISSN 2278-0149

Text 20220301 - IJMERR.PDF Download (3MB)

Abstract

Electro-Hydraulic Actuator (EHA) system is a prevalent mechanism in industrial sectors. This system commonly involving works that required high force such as steel, automotive and aerospace industries. It is a challenging task to acquire precision when dealing with a system that can produce high force. Besides, since most of the mechanical actuator performance varies with time, it is even difficult to ensure its robustness characteristic towards time. Therefore, this paper proposed the industrial’s wellknown controller, which is the Proportional-Integral-Derivative (PID) controller that can improve the precision of the EHA system. Then, an enhanced PID controller, which is the fractional order PID (FOPID) controller will be applied. A classical and metaheuristic optimization methods, which are gradient descent (GD) and particle swarm optimization (PSO) algorithm are used to obtaining the optimal gains of both controllers. In addition, to examine the tracking performance of the designed controllers, the performance of the proposed optimization algorithms is analysed. As a result, in a practical point of view, it can be inferred that the PSO algorithm is capable to generate more practical sense of gains compared with GD, and the precision characteristic of the FOPID is greater than the PID controller.

Item Type:	Article
Uncontrolled Keywords:	Electro-hydraulic actuator (eha), Gradient descent optimization, Particle swarm optimization, Positioning tracking analysis, Robust control design
Divisions:	Faculty of Electrical Engineering
Depositing User:	Sabariah Ismail
Date Deposited:	28 Mar 2023 13:00
Last Modified:	28 Mar 2023 13:07
URI:	http://eprints.utem.edu.my/id/eprint/26411
Statistic Details:	View Download Statistic

Actions (login required)

View Item