Stochastic Stabilization of Markovian Jump Systems with Partial Unknown Transition Probabilities and Actuator Saturation
Stochastic Stabilization of Markovian Jump Systems with Partial Unknown Transition Probabilities and Actuator Saturation
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DOI：
10.1007/s00034-011-9297-6
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发表时间：
2011-04
期刊：
影响因子：
--
通讯作者：
Yijing Wang;Z. Zuo;Yulong Cui
中科院分区：
文献类型：
--
作者：
Yijing Wang;Z. Zuo;Yulong Cui
研究了具有部分未知转移概率和执行器饱和的马尔可夫跳变系统的随机镇定问题。不同于以往的结果是完全了解转移概率，提出了一种新的控制器综合方案，并在均方意义上估计了吸引域。首先建立了保证闭环系统随机稳定的充分条件。然后提出了一个具有LMI约束的优化问题，以确定均方意义上的最大收缩不变量集。最后，通过数值算例验证了该方法的有效性。
The stochastic stabilization problem of Markovian jump systems subject to both partial unknown transition probabilities and actuator saturation is considered in this paper. Different from the previous results where complete knowledge on the transition probabilities is available, a new controller synthesis scheme is proposed as well as an estimate of the domain of attraction in mean square sense. A sufficient condition is first established to guarantee the stochastic stability of the closed-loop system. An optimization problem with LMI constraints is then formulated to determine the largest contractively invariant set in mean square sense. Finally, a numerical example is provided to show the effectiveness of our method.