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摘要
A class of unknown nonlinear systems, which are not in parameter-linearizable expression with uncertain high-order disturbance, are considered. Based on backstepping approach, a multilayer neural network adaptive controller is presented for the nonlinear systems. Approximating nonlinear dynamic is one of the performances of multiplayer neural networks, and the NN weights are turned on-line without more prior knowledge of systems. The NN weight turn law is designed by Lyapunov synthesis approach, and the stabilization of the law is proved. Moreover, a novel quasi-weighted Lyapunov function is modified, which disposels effectively the issue of the singularity-free adaptive control. The simulation result shows that the controller is robust to some nonlinear uncertainties and bounded disturbance, and it can guarantee the global bound of all closed-loop signals.
- 出版日期2004
