An improved method for synchronous control of complex multi-motor system

Abstract

A general mathematic model of multi-motor system working on vector control mode is given. Here, a three-motor synchronous system was taken as the research object, and was proved to be invertible. A method of generalized growing and pruning RBF (GGAP-RBF) neural network inverse for synchronous control of multi-motor system is proposed. The inverse can be constructed by combining the RBF neural network with an integrator, the speed and tension control of three-motor system can be decoupled by combing RBF neural network inverse with the three-motor system. Then, through growing and pruning RBF neural network according to the performance index given, the three-motor variable frequency speed-regulating control system is optimized, solving the problem which can't be done by BP neural network. the method provides a theoretical basis for the research of complex multi-motor synchronous system. The simulation results illustrates it good dynamic and static operation performance.