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H∞ Model Approximation for Uncertain Stochastic Systems: Discrete-Time Case

机译:不确定随机系统的H∞模型逼近:离散情况

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This paper is concerned with the problem ofH∞ model approximation for discrete time systems that possess uncertain stochastic and time delay dependent parameters. In order to get a stable system, our attention is focused on the construction of reduced-order models, which guarantee the corresponding error system to be asymptotically stable and have a prescribed H∞ error performance. Sufficient conditions for the solvability of the problem is obtained via linear matrix inequalities (LMIs) and a coupling non-convex rank constraint set. An explicit parametrization of the desired reduced-order models is presented when these conditions are satisfied. Finally, a numerical example is given to illustrate the effectiveness of the proposed theories.
机译:本文涉及具有不确定随机和时滞相关参数的离散时间系统的H∞模型逼近问题。为了获得一个稳定的系统,我们的注意力集中在降阶模型的构建上,这些模型保证了相应的误差系统是渐近稳定的,并具有规定的H∞误差性能。可通过线性矩阵不等式(LMI)和耦合的非凸秩约束集来获得解决问题的充分条件。当满足这些条件时,将显示所需降阶模型的显式参数化。最后,通过数值例子说明了所提出理论的有效性。

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