BPNN Optimal Robust Control for Vehicle Stability Based on Multiple Layer Perceptron
In order to enhance the stability and robustness of nonlinear vehicle model,an optimal robust control of vehicle stabili-ty based on back propagation neural network with multiple layer perceptron was proposed.Using the four-wheel active steering model,a multiple layer perceptron feed-forward back propagation neural network model was established as the approximator.The optimal robust control was used to adjust the yaw rate and sideslip angle to meet the desired vehicle response.The neural net-work model was established to distinguish the vehicle nonlinear dynamic characteristics and the corresponding optimal feedback was gained through the state variable training.Lyapunov stability method was used to analyze the robustness and stability of the controller,and sliding mode controller was used to track the desired yaw rate and sideslip angle response.Simulation results show that the proposed method can significantly improve the vehicle robustness and control performance.
NETL
NSTL
万方数据
维普
