Abstract
Smart car speed control system is a nonlinear time varying systems, to establish a precise mathematical model isn’t easy, using conventional PID control is not very good. This paper proposes to combine the RBF neural network with fuzzy control by analyzing the smart car system. The collective fuzzy control and neural network control can not only make good use of existing experience knowledge to solve the problem of black box characteristics, but also improve control precision and realize adaptive function in time. The experimental and simulation results show that the proposed direction and speed control algorithm can meet the requirements of the smart car running stably for a short time.
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