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H∞ performance for a class of uncertain stochastic nonlinear Markovian jump systems with time-varying delay via adaptive control method

机译:一类具有时变时滞的不确定随机非线性马尔可夫跳跃系统的H∞性能自适应控制

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This paper studies the H∞ performance for the uncertain recurrent neural networks with both nonlinear external disturbance and Markovian jump parameters, in which the time delay is varying. Our objective is to design robust controllers, that are independent of the time delay, such that the uncertain system is stochastic stable with a generalized H∞ disturbance attenuation level y. For the given uncertain stochastic system, new controllers which are composed of a linear controller and an adaptive controller are proposed to realize H∞ control by introducing a switching function and using the idea of completing square. Based on Ito's differential formula and Lyapunov stability theory, new sufficient conditions are obtained in terms of linear matrices inequalities. A numerical example is constructed to show effectiveness of the designed controller in this paper.
机译:本文研究了具有非线性外部扰动和马尔可夫跳跃参数的不确定递归神经网络的H∞性能,其中时滞是变化的。我们的目标是设计独立于时间延迟的鲁棒控制器,使得不确定系统具有广义H∞干扰衰减水平y的随机稳定。针对给定的不确定随机系统,提出了一种由线性控制器和自适应控制器组成的新型控制器,通过引入开关函数并采用平方求和的思想来实现H∞控制。基于Ito的微分公式和Lyapunov稳定性理论,就线性矩阵不等式获得了新的充分条件。通过算例说明了所设计控制器的有效性。

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