Tong Shaocheng, Liu Changliang, Li Yongming, Zhang Huaguang
Department of Basic Mathematics, Liaoning University of Technology, Jinzhou 121001, China.
IEEE Trans Syst Man Cybern B Cybern. 2011 Apr;41(2):474-85. doi: 10.1109/TSMCB.2010.2059011. Epub 2010 Aug 16.
In this paper, an adaptive fuzzy decentralized robust output feedback control approach is proposed for a class of large-scale strict-feedback nonlinear systems without the measurements of the states. The nonlinear systems in this paper are assumed to possess unstructured uncertainties, time-varying delays, and unknown high-frequency gain sign. Fuzzy logic systems are used to approximate the unstructured uncertainties, K-filters are designed to estimate the unmeasured states, and a special Nussbaum gain function is introduced to solve the problem of unknown high-frequency gain sign. Combining the backstepping technique with adaptive fuzzy control theory, an adaptive fuzzy decentralized robust output feedback control scheme is developed. In order to obtain the stability of the closed-loop system, a new lemma is given and proved. Based on this lemma and Lyapunov-Krasovskii functions, it is proved that all the signals in the closed-loop system are uniformly ultimately bounded and that the tracking errors can converge to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated from simulation results.
本文针对一类无法测量状态的大规模严格反馈非线性系统,提出了一种自适应模糊分散鲁棒输出反馈控制方法。本文中的非线性系统假设具有非结构化不确定性、时变延迟和未知高频增益符号。采用模糊逻辑系统逼近非结构化不确定性,设计K滤波器估计未测量状态,并引入特殊的Nussbaum增益函数来解决未知高频增益符号问题。将反步技术与自适应模糊控制理论相结合,开发了一种自适应模糊分散鲁棒输出反馈控制方案。为了获得闭环系统的稳定性,给出并证明了一个新的引理。基于该引理和Lyapunov-Krasovskii函数,证明了闭环系统中的所有信号都是一致最终有界的,并且跟踪误差可以收敛到原点的一个小邻域内。仿真结果验证了所提方法的有效性。