In this paper, the problem of universal adaptive stabilization is investigated for a class of multi-input multi-output Markovian jump linear systems (MJLSs) with partially unknown transition rates (TRs). The class of systems that we are considering is characterized only by some structural assumptions. Firstly, we show the high-gain stochastic stabilizability, that is, any system belonging to this class can be stabilized by a mode-dependent output feedback controller, provided that the proportional gain for every mode is sufficiently large. Moreover, a universal adaptive high-gain controller, which is not based on identification or any estimation algorithms, is presented. It is shown that this controller ensures the convergence and the boundedness of the closed-loop system signals in the mean square sense. Finally, simulation results are given to illustrate the performance and effectiveness of the proposed approaches. MJLSs, high-gain stabilizability, universal adaptive control, output feedback, partially unknown TRs.

中文翻译：

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一类具有部分未知转移率的多变量马尔可夫跳跃线性系统的通用自适应镇定

在本文中，研究了一类具有部分未知转换率（TR）的多输入多输出马尔可夫跳跃线性系统（MJLS）的通用自适应稳定问题。我们正在考虑的系统类别仅以一些结构性假设为特征。首先，我们展示了高增益随机稳定性，也就是说，只要每个模式的比例增益足够大，属于该类的任何系统都可以通过与模式相关的输出反馈控制器来稳定。此外，提出了一种不基于识别或任何估计算法的通用自适应高增益控制器。结果表明，该控制器确保了闭环系统信号在均方意义上的收敛性和有界性。最后，给出了仿真结果来说明所提出方法的性能和有效性。MJLS，高增益稳定性，通用自适应控制，输出反馈，部分未知 TR。