Neural network control for automatic braking control system

Abstract We have developed an automatic braking control system for automobiles applying a three-layer neural network model. This system enables the vehicle to decelerate smoothly and to stop at the specified position behind the vehicle ahead. This paper focuses on the use of the three-layer neural network model in the automatic braking control system. Because vehicle dynamics is varied by the variations in road conditions or vehicle characteristics, it cannot be represented accurately by mathematical models. According to this reason, the conventional control methods, such as proportional integrative derivative (PID) control, cannot achieve satisfactory control performance. Therefore, we have constructed the neural network adaptive control system based on the feedback error learning method. This learning method enables the system to adapt to the changes in road grade and vehicle weight without using any specific sensors. Experimental results show satisfactory control performance and reveal that the neural network adaptive control system based on the feedback error learning method is available for the automatic braking control system.

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