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Fault-Tolerant Control of Time-Delay Markov Jump Systems With$Ithat{o}$Stochastic Process and Output Disturbance Based on Sliding Mode Observer

机译:具有 $ It hat {o} $ 的时滞Markov跳跃系统的容错控制基于滑模观测器的随机过程与输出扰动

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This paper focuses on the fault-tolerant control problem of Markov jump systems (MJS) with$Ithat{o}$stochastic process and output disturbances. Such a problem widely exists in practical systems such as mobile manipulator systems. Since MJS can suitably describe mobile manipulator systems, in this paper, a new approach based on the MJS model is proposed. First, a proportional-derivative sliding mode observer (SMO) and an observer-based controller are designed and synthesized. Two new theorems are derived to ensure the close-loop stochastic stability and the reachability of the sliding mode surface. Compared with the existing works, the system model is more general, which could describe a larger variety of plants or processes. The controller design procedure is simplified by solving the sliding mode parameters and the controller gain simultaneously with only one linear matrix inequality problem. In addition, the augmented fault vector can be reconstructed by employing a descriptor SMO. Simulations are provided to demonstrate the validity of the derived theorems and the effectiveness of the proposed algorithm.
机译:本文重点研究具有 n $ It hat {o} $ n随机过程和输出干扰。在诸如移动操纵器系统的实际系统中广泛存在这样的问题。由于MJS可以恰当地描述移动机械手系统,因此本文提出了一种基于MJS模型的新方法。首先,设计并合成了比例微分滑模观测器(SMO)和基于观测器的控制器。推导了两个新的定理,以确保闭环随机稳定性和滑模面的可达性。与现有作品相比,系统模型更为通用,可以描述更多种类的工厂或过程。通过仅求解一个线性矩阵不等式问题,即可同时解决滑模参数和控制器增益,从而简化了控制器设计过程。另外,可以通过使用描述符SMO来重建增强的故障向量。仿真结果证明了所推导定理的有效性以及所提出算法的有效性。

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