Three-Motor Synchronous Speed-Regulation System Based on RBF Neural Network Control

Three-motor synchronous speed-regulation system is a multi-input multi-output (MIMO), nonlinear, and coupling complex control system. This paper focuses on the system of induction motors powered by current-track type SPWM transducers, establishes the mathematical model of the system in the way of analytical expression. Self-tuning PID controllers based on RBF neural network and neuron decoupling compensator are adopted to realize the adaptive decoupling control of speed and tension. Simulation and experiment results show that compared with traditional PED constant parameters control, the control system can obtain optimal parameters of the PID controller according to online identification of the RBF network, realize the better decoupling control of speed and tension, and possess better dynamic and static performance and good robustness. Thus, the method presented in the paper meets the requirements of many industrial control environments, with good application prospects. And it can be extended to the usual multimotor (n≥3) system.