Optimization and Design of Maglev System PID Controller Based on Particle Swarm Optimization Algorithm

In order to improve the nonlinear and unstable characteristics of maglev systems, two nonlinear subsystems with different structures were transformed into linear ones with the same structure by differential geometry method, and then a PID controller that is based on the standard particle swarm optimization (PSO) was built. For the PSO algorithm, the fixed inertia weight (FIW), linear descend inertia weight (LIW), and linear differential descend inertia weight (LDW) were comparatively studied through simulation; among them the FIW was found more suitable and hence selected for electromagnet 1 and electromagnet 2. After optimization of controller parameters, the value of the FIW parameter C for electromagnets 1 and 2 was set to 0.5 and 0.49, respectively. In addition, a fuzzy comprehensive evaluation model was built to evaluate the anti-interference performance of the electromagnets 1 and 2, revealing that the two electromagnets both have a good anti-interference ability, and the membership degree of good is 0.561 9. Experimental results show that the optimized maglev system has a fairly good robustness.