Robust adaptive fuzzy control for a class of stochastic nonlinear systems with dynamical uncertainties
Robust adaptive fuzzy control for a class of stochastic nonlinear systems with dynamical uncertainties
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DOI：
10.1016/j.jfranklin.2012.09.012
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发表时间：
2012-12
期刊：
影响因子：
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通讯作者：
Tong Wang;Shaocheng Tong;Yong-ming Li
中科院分区：
文献类型：
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作者：
Tong Wang;Shaocheng Tong;Yong-ming Li
针对一类具有未知非线性函数、动态不确定性和无状态测量的不确定随机非线性系统，提出了一种鲁棒自适应模糊输出反馈控制方法。利用模糊逻辑系统逼近未知非线性函数，设计模糊状态观测器对未测状态进行估计。为解决系统的动态不确定性问题，将动态信号与供给函数变化相结合的特性引入退步递推设计技术，构造了一种新的鲁棒自适应模糊输出反馈控制方案。通过合理选择设计参数，证明了闭环系统的所有解在概率上都是有界的，并且观测器误差和系统输出收敛到原点的一个小邻域内。通过两个仿真实例验证了所提控制方法的有效性。
In this paper, a robust adaptive fuzzy output feedback control approach is developed for a class of uncertain stochastic nonlinear systems with unknown nonlinear functions, dynamical uncertainties and without the measurements of the states. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy state observer is designed for estimating the unmeasured states. To solve the problem of the dynamical uncertainties, the dynamical signal combined with changing supply function is incorporated into the backstepping recursive design technique, and a new robust adaptive fuzzy output feedback control scheme is constructed. It is proved that all the solutions of the closed-loop system are bounded in probability, and the observer errors and the output of the system converge to a small neighborhood of the origin by choosing design parameters appropriately. Two simulation examples are provided to demonstrate the effectiveness of the proposed control approach.