Direct adaptive neural networks control for a class of uncertain nonlinear systems with prespecified tracking performance

摘要：

In this paper, we propose an adaptive control scheme for a class of uncertain nonlinear systems in strict-feedback form. By combining dynamic surface control technique with neural networks, explosion of complexity in backstepping design is avoided, and only one parameter is needed to be updated. Moreover, by applying performance function and output error transformation, the prespecified tracking performance, i.e., the convergence rate, the allowable maximum overshoot and the steady state error, can be achieved. It is proved that semi-global stability of the closed-loop system can be guaranteed. Finally, simulation results are given to demonstrate the efficiency of the proposed scheme.

关键词： Dynamic Surface Control Backstepping Design Adaptive Neural Networks Control Tracking Performance

作者: YANG Pengsong SUN Xiuxia DONG Wenhan YU Xiuduan

作者单位: Engineering Institute, Air Force Engineering University, Xian 710038, China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 2981-2986

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）