Research On Design Of Control Systems With Particle Swarm Optimization Algorithm

As the advancement of the science and technology and development of the industrial manufactures, the traditional control methods can not get the satisfying performance on the control precision and response characteristic for non-linear, multi-dimensional and uncertain complex industrial processes. It is one of the effective methods to introduce intelligent optimization methods to the control system for guiding the design of control systems and identifying parameters of the process model.Recently, particle swarm optimization (PSO) algorithm comes forth as another intelligent algorithm. It is simple with concept, parameters and implementation. PSO and its researchment actuality are summarized firstly, then PSO is applied to optimize and design the control systems. The main contributions given in this dissertation are as follows:(1) PSO is proposed to optimize the parameters of the conventional PID controller and robust PID controller. The simulation results of the different control systems show that the optimal PID controller based on PSO has a satisfying performance and is better than the conventional PID controller based on the conventional tuning method.(2) Parameters estimation of system model have been always the hot issue in the automatic control field. PSO is proposed to estimate parameters of MSN. The effectiveness of PSO is tested by examples. The simulation results show that PSO provides the attractive method to the estimation of parameters of system model.(3) Aiming at the complex nonlinear system, a PID self-adaptive control method based PSO is stated. Using PSO to optimize the on-line PID parameters, desirable control effect is obtained. Simulation results show the validity of the method. Finally some conclusions and future researches are drawn in this dissertation.