Adaptive neural control for a class of stochastic non-strict-feedback nonlinear systems with time-delay

作者：Sun, Yumei; Chen, Bing^*; Lin, Chong; Wang, Honghong

来源：Neurocomputing, 2016, 214: 750-757.

DOI：10.1016/j.neucom.2016.06.060

• Neural adaptive control
• Stochastic nonlinear systems
• Non-strict-feedback
• Backstepping
• Time-delay
• Lyapunov-Krasovskii functional

This paper addresses adaptive neural control for a class of non-strict-feedback stochastic nonlinear systems with time delays. An important structural property of radial basis RBF) neural networks (NNs) is introduced to overcome the design difficulty from the non-strict-feedback structure. The Lyapunov-Krasovskii functional is used for control design and stability analysis. Further, a backstepping-based adaptive neural control strategy is proposed. The suggested adaptive neural controller guarantees that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of the origin. Simulation results demonstrate the effectiveness of the proposed approach.

• 出版日期2016-11-19
• 单位青岛大学; 山东科技大学