The Research Of The Application Of Parameters' Auto-tuning PID Controller In Suspension Control

Suspension control is the key technology of maglev vehicle research. PID control is more often used in suspension control, but due to the time-varying uncertainty of the suspension train, the conventional PID control algorithm can hardly achieve the desired effect. In this dissertation, the application of parameters' auto-tuning PID control algorithm is studied, and a self-optimizing PID controller and a parameters' fuzzy auto-tuning PID controller are designed. The parameters of PID controller are adjusted online, making the performance of the levitation control system greatly improved.At first, a single electro-magnet suspension system is modeled in this article, obtaining a non-linear model. The performance of the suspension control is analyzed through the linearization of the system around the equilibrium point, and the design of PID controller is also introduced. In order to overcome the deficiency of the conventional PID controller, a PID parameters' self-tuning algorithm is put forward; and a self-optimizing algorithm and a PID fuzzy self-tuning algorithm are chosen to be applied in suspension control. Concerning the shortcoming of the large amount of calculation when using the self-optimizing algorithm, a PID normalized self-optimizing algorithm, combing pattern recognition algorithm, is proposed. As the fuzzy rules improve, another improved high accuracy PID fuzzy self-tuning controll algorithm is proposed in suspension control.Through Matlab simulation and experiments, we can conclude that: comparing with the conventional PID controller, the dynamic and static performances of the self-optimizing PID controller and fuzzy self-tuning PID controller have been significantly improved; especially the fuzzy self-tuning PID controller achieves the best performance.