Abstract: The dynamic model of eight Degrees of Freedom (8D) Four-wheel Steering (4WS) vehicle was established. Using the theory of artificial neural network, a Radial Basis Function Neural Network (RBFNN) controller was designed and it was trained by the direct close-loop training method off-line. In order to overcome the shortcomings of poor adaptability caused by off-line training, a single neuron adaptive PSD controller was also designed. The RBFNN controller and the single neuron adaptive PSD controller composed a compound control system to jointly complete the steering control of 4WS vehicle. Simulation experiments were carried out by combining the RBFNN compound controller with the 8D 4WS vehicle dynamic model. Results show that the designed RBFNN compound controller can effectively improve the steering stability of 4WS vehicle both in constant speed and variable speed conditions.

Key words: vehicle engineering, four-wheel steering, stability control, radial basis function neural network, single neuron adaptive PSD control