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Recursive Robust Regulator for Discrete-Time Markovian Jump Linear Systems

机译:离散马尔可夫跳跃线性系统的递归鲁棒调节器

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In this paper, we propose a robust regulator for discrete-time Markovian jump linear systems (DMJLS) subject to structured parameter uncertainties. States of Markov chain are considered known at each instant and the transition probabilities matrix is time-varying. The framework proposed to deal with this problem is developed through a regularization approach based on robust least-squares and penalty functions. Recursive solutions in terms of coupled Riccati equations, which do not depend on any auxiliary parameter to be tuned, are provided. These equations resemble the recursive solutions of DMJLS standard regulators when the system is not subject to uncertainties. Conditions for convergence and stability of this robust regulator are established. Numerical examples present comparative studies considering the proposed robust regulator, the standard linear quadratic regulator, and an H∞-controller for DMJLS.
机译:在本文中,我们针对结构参数不确定性,为离散时间马尔可夫跳跃线性系统(DMJLS)提出了一种鲁棒的调节器。认为马尔可夫链的状态在每个时刻都是已知的,并且转移概率矩阵是随时间变化的。通过基于鲁棒最小二乘和罚函数的正则化方法,开发了解决该问题的框架。提供了不依赖于任何要调整的辅助参数的耦合Riccati方程的递归解。当系统不受不确定性影响时,这些方程式类似于DMJLS标准调节器的递归解。建立了该鲁棒调节器的收敛性和稳定性的条件。数值示例提供了比较研究,其中考虑了拟议的鲁棒调节器,标准线性二次调节器和DMJLS的H∞控制器。

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