Adaptive NN output-feedback stabilization for a class of stochastic nonlinear strict-feedback systems

作者：Li Jing; Chen Weisheng; Li Junmin; Fang Yiqi

来源：ISA Transactions, 2009, 48(4): 468-475.

DOI：10.1016/j.isatra.2009.05.004

• Neural network
• Output-feedback stabilization
• Nonlinear observer
• Stochastic nonlinear strict-feedback systems
• Adaptive Backstepping

In this paper, the adaptive neural network output-feedback stabilization problem is investigated for a class of stochastic nonlinear strict-feedback systems. The nonlinear terms, which only depend on the system output, are assumed to be completely unknown, and only an NN is employed to compensate for all unknown upper bounding functions, so that the designed controller is more simple than the existing results. It is shown that, based on the backstepping method and the technique of nonlinear observer design, the closed-loop system can be proved to be asymptotically stable in probability. The simulation results demonstrate the effectiveness of the proposed control scheme.

• 出版日期2009-10
• 单位西安电子科技大学