Application of harmony search algorithm and particle swarm optimization for tuning proportional differential fuzzy controller for position control in pneumatic actuator

Abstract

Pneumatic actuator system is highly nonlinear and time varying due to many factors such as friction, load variations, air compressibility, dead-time and leakage. Therefore handling and controlling the pneumatic actuator required a specific knowledge and suitable control strategy. In this project, the optimization of pneumatic actuator system which primarily consists of proportional valve and double acting cylinder are presented. The optimization methods that are chose is Harmony Search Algorithm (HSA) which recently introduced and developed and the other one is Particle Swamp Optimization (PSO); population based stochastic optimization technique that inspired by social behaviour of bird flocking or fish schooling. The optimization techniques will be tested by simulation using MATLAB Simulink and then validated by real time experiment. The tracking performances of both techniques are compared and the results show that the HSA provides a better tracking performance compared to the PSO.