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Observer-based adaptive fuzzy backstepping dynamic surface control design and stability analysis for MIMO stochastic nonlinear systems

机译:MIMO随机非线性系统基于观测器的自适应模糊逆推动态曲面控制设计与稳定性分析

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In this paper, an adaptive fuzzy backstepping output feedback dynamic surface control (DSC) approach is developed for a class of multiinput and multioutput (MIMO) stochastic nonlinear systems with immeasurable states. Fuzzy logic systems are firstly utilized to approximate the unknown nonlinear functions, and then a fuzzy state observer is designed to estimate the immeasurable states. By combining adaptive backstepping technique and dynamic surface control (DSC) technique, an adaptive fuzzy output feedback backstepping DSC approach is developed. The proposed control method not only overcomes the problem of explosion of complexity inherent in the backstepping design methods, but also the problem of the immeasurable states. It is proved that all the signals of the closed-loop adaptive control stochastic system are semiglobally uniformly ultimately bounded (SUUB) in probability, and the observer errors and the output of the system converge to a small neighborhood of the origin. Simulation results This work was supported by the National Natural Science Foundation of China (No. 61074014), and the Outstanding Youth Funds of Liaoning Province (No. 2005219001). are provided to show the effectiveness of the proposed approach.
机译:本文针对一类具有不可测量状态的多输入多输出(MIMO)随机非线性系统,开发了一种自适应模糊反推输出反馈动态表面控制(DSC)方法。首先利用模糊逻辑系统对未知的非线性函数进行近似,然后设计模糊状态观测器来估计不可测量的状态。通过将自适应反推技术与动态表面控制技术相结合,开发了一种自适应模糊输出反馈反推DSC方法。所提出的控制方法不仅克服了反推设计方法固有的复杂性激增的问题,而且克服了不可估量状态的问题。证明了闭环自适应控制随机系统的所有信号在概率上都是半全局一致的有界极限(SUUB),并且观察者误差和系统的输出收敛到原点的一个小邻域。模拟结果这项工作得到了国家自然科学基金(No. 61074014)和辽宁省优秀青年基金(No. 2005219001)的支持。提供以显示该方法的有效性。

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