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

• 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; http://eprints.utem.edu.my/id/eprint/25979/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=121057

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.