Adaptive Backstepping Sliding Mode Control for Nonlinear Systems with Neural Networks

摘要：

The backstepping control is investigated for a class of unknown nonlinear systems in parametric-purefeedback form. Neural networks(NNs) are applied to approximate the unknown dynamics. The adaptive laws of the weights of NN and the ideal sliding mode are derived in the sense of Lyapunov function, so the stability can be guaranteed. The proposed control not only relaxes the assumptions of nonlinear systems, but also holds the robustness. Moreover, the tracking error can converge to zero asymptotically. Simulations illustrate the effectiveness of the proposed approach.

关键词： backstepping control adaptive control sliding mode neural networks nonlinear systems

作者: Hongmei Zhang Guoshan Zhang

作者单位: School of Electrical Engineering & Automation, Tianjin University, Tianjin 300072, China Shenyang In School of Electrical Engineering & Automation, Tianjin University, Tianjin 300072, China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 3642-3646

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）