Performance Analysis of Position Tracking Control with PID Controller using an Improved Optimization Technique Chai Mau Shern, Rozaimi Ghazali, Chong Shin Horng, Hazriq Izzuan Jaafar, Chong Chee Soon Center for Robotics and Industrial Automation, Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Melaka, Malaysia Email: {maushern, halklezt}@gmail.com, {rozaimi.ghazali, horng, hazriq}@utem.edu.my Yahaya Md Sam Department of Control and Mechatronics Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor, Malaysia Email: {yahaya}@fke.utm.my Abstract— An Electro-Hydraulic Actuator (EHA) system is usually utilized in production industry such as automotive industry which requires precision, high force and long operating hours. When dealing with the production of engineering parts that require precision, high force and long operating hours, a controller is usually required. It is observed from the literature, an appropriate tuning technique is essential in order to obtain optimal controller’s performance. Therefore, a computational tuning technique, namely Priority-based Fitness Particle Swarm Optimization (PFPSO) is proposed to obtain the parameters of the Proportional-Integral-Derivative (PID) controller in this paper. The performance of the EHA system will be evaluated and compared based on the priority characters of the PFPSO tuning technique, which included settling time and overshoot percentage that affect the output results of the EHA system. As a result, it is observed that the priority based on settling time produced a better result, which enhances the steady-state performance of the EHA system that fulfills the requirement of the precision control. 1 Index Terms—Electro-hydraulic actuator system; particle swarm optimization; priority-based fitness; position tracking control I. INTRODUCTION The dynamics of an actuator are usually generated through a different type of energy sources, including hydraulic, pneumatic and electric. As compared to the pneumatic and electrical actuators, a hydraulic actuator is widely used in industries due to its capability in generating large torque, high power and accurate positioning with fast motion [1]. The hydraulic actuator is an actuator system that utilizes pressurized hydraulic fluid, which is functioning as a drive or transmission system in generating a dynamic [2]. However, the nonlinear electro-hydraulic system is suffering from nonlinearities and time-varying characteristics such as high speed, outburst starting and Manuscript received January 5, 2018; revised February 17, 2019. stopping dynamic that produced by the flow and the pressure in the hydraulic system. The nonlinear properties causing a backlash in the control valve, actuator friction, distinction in fluid volume that make the system models and controller designs more complex [3]. The nonlinear properties that are produced through pressure and flow rate of the hydraulic system required a suitable controller to achieve better performances. In the previous works, there are many types of control techniques have been reported, which can be utilized to control the tracking capability of a nonlinear electro- hydraulic actuator system. Each of the control techniques required a proper tuning technique and some of the advanced tuning techniques have been reported recently such as Particle Swarm Optimization (PSO) [4-7], Genetic Algorithm (GA) [8-10], and Differential Evolution (DE) [11,12]. Instead of using a conventional PSO tuning technique, a different tuning method has been implemented in the gantry crane system which is the PSO based on the priority-based fitness schemes as proposed in [13]. The priority-based fitness Particle Swarm Optimization (PFPSO) has been utilized to obtain the parameters of the Proportional-Integral-Derivative (PID) that used to control the trolley position and the Proportional- Derivative (PD) that control the oscillation of the payload. The accuracy and the robustness toward the disturbance for the trolley’s position and the payload’s oscillation have been significantly improved. In this paper, the effect of the PFPSO algorithm applied to the EHA system will be analysed. Rather than searching for the entire particles fitness, the algorithm will be executed by exploring the fitness based on the priorities, including the settling time and the overshoot of the EHA system. The priority that generates better steady-state performance will be referred since the accuracy is considered as the highest priority in the performance evaluation of the EHA system. International Journal of Mechanical Engineering and Robotics Research Vol. 8, No. 3, May 2019 © 2019 Int. J. Mech. Eng. Rob. Res 401 doi: 10.18178/ijmerr.8.3.401-405