摘要
针对一类控制增益未知的不确定非线性系统的输出跟踪控制问题,提出了一种自适应神经网络动态面控制器设计方案.通过采用基于状态参考的反推控制策略,放松了对用于设计期望虚拟控制律的函数项的限制.在递推设计过程,设计的参数自适应律为光滑函数,满足了应用Nussbaum增益设计技术的前提条件;引入了一阶低通滤波器,降低了控制器复杂性,减小了计算量.理论分析和仿真结果均表明所提控制方案能够使得闭环系统所有信号和跟踪误差半全局一致终结有界.
An adaptive neural network dynamic surface control scheme is proposed to deal with the output traclong control problem of a class of uncertain nonlinear systems with unknown control gain. Based on the backstepping control theory, combined with the idea of reference state, the restrictions on the system nonlinearities which are used to design the virtual controllers are released. The adaptive laws are designed to be smooth to match the prerequisite conditions of applying the Nussbaum gain design techniques in each step. The first order filter is adopted to simplify the procedure of designing the controller, and reduce the complexities and the calculations of the controller. The results of theoretical analysis and simulation show that all the signals in the closed loop systems and the tracking error are semi-globally uniformly ultimately bounded.
出处
《信息与控制》
CSCD
北大核心
2013年第6期686-692,共7页
Information and Control
基金
国家自然科学基金资助项目(51175510)
航空科学基金资助项目(20111396011)
