具有动态和静态关联项大系统的鲁棒分散自适应镇定

对于一类具有动态和静态关联项的大系统，利用MT-滤波器和反推设计方法设计了一种鲁棒分散自适应输出反馈控制器．在各子系统为最小相位、静态关联项满足Lipschitz条件、动态关联项稳定且严格正则的假设下，证明了闭环系统的所有信号全局一致有界，且除了参数估计外的其他信号皆以指数速率收敛到零，该结果好于其他相关文献中的结果，仿真结果进一步验证了该方法的有效性。

Robust decentralized adaptive stabilization for large-scale systems with dynamic and static interconnections

For a class of large-scale systems with dynamic and static interconnections, a robust decentralized adaptive output-feedback controller is designed by using the MT-filters and backstepping design method. Under the (assumptions) that each subsystem is minimum phase, that the static interconnections satisfy Lipschitz condition, and that dynamic interconnections are stable and strictly proper, it is shown that all signals in the closed-loop system are globally uniformly bounded, and all the signals except for the parameter estimates converge to zero exponentially fast. The result is better than those obtained in other relative papers. A simulation example shows the effectiveness of the method.