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Robust fuzzy control for uncertain discrete-time nonlinear Markovian jump systems without mode observations

机译:无模式观测的不确定离散非线性马尔可夫跳跃系统的鲁棒模糊控制

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This paper studies the robust fuzzy control problem of uncertain discrete-time nonlinear Markovian jump systems without mode observations. The Takagi and Sugeno (T-S) fuzzy model is employed to represent a discrete-time nonlinear system with norm-bounded parameter uncertainties and Markovian jump parameters. As a result, an uncertain Markovian jump fuzzy system (MJFS) is obtained. A stochastic fuzzy Lyapunov function (FLF) is employed to analyze the robust stability of the uncertain MJFS, which not only is dependent on the operation modes of the system, but also directly includes the membership functions. Then, based on this stochastic FLF and a non-parallel distributed compensation (non-PDC) scheme, a mode-independent state-feedback control design is developed to guarantee that the closed-loop MJFS is stochastically stable for all admissible parameter uncertainties. The proposed sufficient conditions for the robust stability and mode-independent robust stabilization are formulated as a set of coupled linear matrix inequalities (LMIs), which can be solved efficiently by using existing LMI optimization techniques. Finally, it is also demonstrated, via a simulation example, that the proposed design method is effective. (c) 2006 Elsevier Inc. All rights reserved.
机译:本文研究了无模式观测的不确定离散非线性马尔可夫跳跃系统的鲁棒模糊控制问题。 Takagi和Sugeno(T-S)模糊模型用于表示具有范数有界参数不确定性和Markovian跳跃参数的离散时间非线性系统。结果,获得了不确定的马尔可夫跳跃模糊系统(MJFS)。采用随机模糊Lyapunov函数(FLF)分析不确定MJFS的鲁棒稳定性,它不仅取决于系统的运行模式,还直接包括隶属函数。然后,基于这种随机FLF和非并行分布补偿(non-PDC)方案,开发了一种与模式无关的状态反馈控制设计,以确保对于所有允许的参数不确定性,闭环MJFS随机稳定。为鲁棒稳定性和与模式无关的鲁棒稳定性提出的充分条件被公式化为一组耦合线性矩阵不等式(LMI),可以使用现有的LMI优化技术有效地解决这些问题。最后,还通过仿真实例证明了所提出的设计方法是有效的。 (c)2006 Elsevier Inc.保留所有权利。

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