THE FORCE TRACKING CONTROL OF ELECTRO-HYDRAULIC SYSTEM BASED ON PARTICLE SWARM OPTIMIZATION

This paper presents the optimal gains of backstepping controller by using the particle swam optimization technique. The mathematical model is developed by Newton's second law, compressible fluid flow and flow rates of valve. The control law is formulated by employing a Control Lyapunov Function. The core feature of this paper is the combination of the backstepping and particle swam optimization for optimal performance of controller. The controller gains are determined in automatic selection gains by minimizing the integral of time multiplied by absolute error function on step input. The fitness value can be guaranteed to the convergence of controller gains. The implementations are separated into two cases which are the real and estimated state feedbacks. The experiment has illustrated to find optimal controller gains. The results are also compared with the tracking response of real and estimated state measures in step and square signal. The results show a better tracking performance by using the strong particle swarm optimization (PSO) algorithm.