CHEN Tao, CHEN Dong. Lateral control of intelligent vehicle based on neural networks sliding mode[J]. 2017, 36(5): 63-67. DOI: 10.13873/j.1000-9787(2017)05-0063-05.
The RBF neural networks sliding mode control method is proposed to solve the highly nonlinear dynamic characteristic and parametric uncertain properties of the intelligent vehicle model as well as the low control precision and poor robustness caused by massive external interference during driving. A two degrees of freedom( DOF) linear vehicle model is built along with a seven DOF non-linear vehicle model. A new state equation is derived based on traditional state equation of the two DOF vehicle control method and the corresponding controller is designed. The Lyapunov stability theory is involved to derive the weights of the neural network and the stability of the control system is verified. Simulation results show that the proposed method has higher control precision and stronger robustness compared with the traditional sliding mode control method.