具有未建模动态的自适应神经网络动态面控制

Adaptive neural-network dynamic surface-control with unmodeled dynamics

中文关键词  未建模动态  自适应控制  动态面控制  严格反馈非线性系统  神经网络控制

英文关键词  unmodeled dynamics  adaptive control  dynamic surface-control  strict-feedback nonlinear systems  neuralnetwork control

中文摘要

      对一类具有未建模动态的严格反馈非线性系统, 提出一种自适应神经网络动态面控制方案. 该方案将动态面控制方法扩展到具有未建模动态的严格反馈非线性系统的控制器设计中, 拓展了动态面控制方法的应用范围. 利用动态面控制方法引入的紧集来处理未建模动态对于系统的影响. 利用Young’s不等式, 提出两种自适应参数调节方案. 与现有研究结果相比, 有效地减少了可调参数的数目, 放宽了动态不确定性的假设, 无需虚拟控制增益系数导数的信息. 通过理论分析, 证明了闭环控制系统是半全局一致终结有界的, 且跟踪误差收敛到原点的一个小邻域内.

英文摘要

      The adaptive neural-network dynamic surface-control is presented for a class of nonlinear systems in a strictfeedback form with unmodeled dynamics. This scheme extends the routine method of dynamic surface-control to the strict-feedback nonlinear systems with unmodeled dynamics, thus broadens the application of the dynamic surface-control. The effects of unmodeled dynamics are reduced by introducing the defined compact set to dynamic surface-control design. Using Young’s inequality, we developed two adaptive parameter-tuning schemes. Compared with the existing results, the proposed approach reduces the number of adjustable parameters effectively, relaxes constrain on dynamic uncertainties and eliminates the requirements of the derivatives of virtual control coefficients. By theoretical analysis, the closed-loop control system is shown to be semi-globally uniformly ultimately bounded, with the tracking error converging to a small neighborhood of the origin.