Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system

Ghani, Muhamad Fadli (2023) Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system. Doctoral thesis, Universiti Teknikal Malaysia Melaka.

	Text (24 Pages) Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system.pdf - Submitted Version Download (571kB)
	Text (Full Text) Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system.pdf - Submitted Version Restricted to Registered users only Download (23MB)

Abstract

The electrohydraulic actuator (EHA) system generates a trajectory by transferring high force densities in the form of pressurized fluid flows to a hydraulic actuator. Moreover, the sliding mode control (SMC) approach has been discovered as a potential method for the EHA trajectory tracking control system. However, high-frequency proportional valve activity has occurred during the practical application of the conventional SMC approach, resulting in tracking performance degradation. Furthermore, a preferable SMC sliding surface design is necessary to improve the precision of trajectory tracking performance, and the SMC designs involve complicated procedure and mathematical formulations. Therefore, this thesis proposes an optimized fuzzy logic (FL) SMC with a proportional-integral-derivative (PID) structure for trajectory tracking control in an EHA system. The proposed control strategy was designed with the switching function modification based on an FL approach in the conventional SMC algorithm called FLSMC. A particle swarm optimization (PSO) algorithm was implemented as the FLSMC design involves a complicated procedure and mathematical formulations to obtain the optimal value of the designed control variables. By adopting the same design concept, the conventional SMC approach was developed for performance comparisons. Furthermore, in an attempt to achieve the objectives of precise trajectory tracking control, a hybrid control structure of FLSMC and PID feedback control (FLSMCPID) is proposed and implemented. Due to the difficulty of concurrent hybrid design, the PSO algorithm was employed to determine the optimal control variables value. For performance comparisons with the proposed hybrid control strategy, a hybrid conventional SMC and PID feedback control (SMCPID) was established by using the same design concept. Simulations utilizing a linear EHA system model obtained using the grey-box identification approach and experimentation on an EHA system workbench for various trajectories and under the consequences of variation in supply pressure were conducted to evaluate the performance of the proposed control strategies. A linear type actuation of the EHA system using a single-ended cylinder controlled by a proportional valve was considered in the experimental design. The simulation and experimental results demonstrate that higher effectiveness, precision, and robustness were achieved by the EHA system with the FLSMC and FLSMCPID as compared to the established conventional SMC and SMCPID approaches, respectively. Moreover, the experimental results verified that the EHA system with the FLSMCPID achieved 82.1%, 78.9%, 94.8%, and 88.8% improvement in the precision tracking control for 0.25 Hz sinusoidal, multi-sinusoidal, point-to-point, and chaotic trajectories, respectively, and enhanced the robustness by 33.3% compared to the FLSMC control strategy. It is envisaged that the proposed FLSMC and FLSMCPID control strategies can be utilized for effective, precise, and robust tracking control of various EHA systems.

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Electrohydraulic Actuator (EHA), Trajectory tracking control, Sliding Mode Control (SMC)
Subjects:	T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery
Divisions:	Library > Tesis > FKE
Depositing User:	MUHAMAD HAFEEZ ZAINUDIN
Date Deposited:	13 Dec 2024 11:44
Last Modified:	13 Dec 2024 11:44
URI:	http://eprints.utem.edu.my/id/eprint/28262
Statistic Details:	View Download Statistic

Actions (login required)

View Item