Design and Simulation of Intelligent PID Controller Based on Particle Swarm Optimization

Aiming at the problem that it is difficult to confirm the parameters of the PID controller and the parameters can not be changed once identified, an intelligent PID control method is proposed. According to the size of the system error, this algorithm controls the system with different subsections of different parameters, by using the particle swarm optimization (PSO) to optimize the parameters of the PID controller to solve the problems, such as lag, time-variety and nonlinearity. A new evaluation function including the system adjusting time, rise time, over-shoot, and system error is defined. A group of parameters of the PID controller that minimize the evaluation function is calculated rapidly by searching in the given controller parameters area. Numerical simulations show that the controller can easily be applied to the first-order and second-order systems with time delay and its performance is also better than the classic PID optimized by PSO.