Car-following collision prevention control using recurrent cerebellar model articulation controller

This paper presents an adaptive recurrent cerebellar-model-articulation-controller (RCMAC) for the car-following collision prevention system. In this control system, a RCMAC is the main tracking controller used to mimic a perfect control law and a compensated controller is designed to compensate for the difference between the perfect control law and the RCMAC. The online adaptive laws of the control system are derived based on the Lyapunov stability theorem, so that the stability of the system can be guaranteed. Finally, the proposed adaptive RCMAC is applied for the car-following collision prevention control. Simulation results show that this method can provide a safe car-following control. Moreover, the presented adaptive RCMAC controller can solve the problems of the oscillations for final distance between the leading vehicle (LV) and the following vehicle (FV).