Adaptive neural switching control with average dwell-time technique

摘要：

In this paper, an adaptive neural control problem for a class of switched nonlinear systems with unknown control gain is presented. RBF neural networks (RBF NNs) are used as a tool for modeling the unknown control law up to a small error tolerance. Based on the proposed control scheme with average dwell-time technique, it’s proved that the resulting closed-loop system is asymptotically Lyapunov stable such that the output tracking error performance is well obtained. Finally, a simulation example demonstrates the effectiveness and robustness of the proposed controller.

关键词： Adaptive neural control Switched nonlinear systems RBF neural networks Average dwell-time

作者: YU Lei FEI Shumin

作者单位: School of Mechanical and Electric Engineering; Soochow University, Suzhou , 215021, China Key Labora School of Automation, Southeast University, Nanjing, 210096

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: 339-342

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）