Study on Improved Expert PID Controller Based on PSO Algorithm for Maglev Transportation System with Time Delay

Time delay is one of the most important aspects of the suspension control performance impact in maglev transportation system (MTS). By using the traditional PID control, the problem is that it is difficult to confirm the PID parameters and have long settling time, even appear the chaotic phenomenon. However, using Expert PID (EPID) control method produced over-fitting to initial assignments, local optimum induced easily and slow convergence rate problem. Based on the global optimization feature of PSO algorithm, it has been adopted to optimize the initial values of Expert PID control in this paper. An intelligent control algorithm for the maglev transportation system was put forward based on Expert PID optimized by Particle Swarm Optimization algorithm (EPID-PSO). The expert rule is that if the absolute value of the error trended to decrease, the PID current control kept its maintenance; if not, then the PID current control applied strong functions. Under this rule, the dynamic error is reduced, and the performance of time delay is improved. Simulation results by MATLAB proved that the control scheme compared with EPID control and PSO-PID control has good robustness, shorter adjustment time, faster response time, achieving better quality of control.