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Stabilization of positive Markovian jump systems with input saturation: A linear programming approach

机译:具有输入饱和度的正马尔科夫跳跃系统的稳定:一种线性规划方法

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This paper proposes a linear programming (LP) approach for stabilization of positive Markovian jump systems (PMJSs) with input saturation. First of all, we derive the sufficient conditions for stabilization of PMJSs with input saturation based on the linear co-positive Lyapunov function. However, since the decision variables in the obtained conditions are mutually coupled, the conditions are not linear. Therefore, to obtain the condition that can be solved by the LP, we propose the methods to properly choose the decision variables. Furthermore, we give a process to acquire the largest domain of attraction. Finally, we suggest two numerical examples to illustrate the validity of the proposed methods.
机译:本文提出了一种线性规划(LP)方法,用于稳定具有输入饱和度的正马氏跳跃系统(PMJSs)。首先,我们基于线性共正Lyapunov函数推导了具有输入饱和度的PMJS稳定的充分条件。但是,由于所获得的条件中的判定变量相互耦合,所以条件不是线性的。因此,为了获得可以由LP来解决的条件下,我们提出的方法来选择正确的决策变量。此外,我们给出了获取最大吸引力领域的过程。最后,我们提出两个数值例子来说明所提方法的有效性。

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