基于 RBFNN 的智能车辆转向系统的预设性能控制.

The prescribed performance tracking control problem of intelligent vehicle steering system with model nonlinearity and parameter uncertainty is studied. The RBFNN (Radial Basis Function Neural Network) is used to approximate the uncertain nonlinearity in the steering system. The prescribed performance controller is designed for the steer-by-wire system of intelligent vehicle based on the barrier Lyapunov function technology. In the design of the controller, the dynamic gain technology is used to compensate the effect of unknown control gain on the system control performance. Finally, the stability of the system is analyzed by Lyapunov method, and it is proved that the tracking error of the front wheel angle can converge to the prescribed neighborhood of the origin within the prescribed time under the action of the proposed controller. The rationality of the control method is verified by numerical simulation and vehicle experiment. [ABSTRACT FROM AUTHOR]