Fuzzy-Adaptive Decentralized Output-Feedback Control for Large-Scale Nonlinear Systems With Dynamical Uncertainties
Fuzzy-Adaptive Decentralized Output-Feedback Control for Large-Scale Nonlinear Systems With Dynamical Uncertainties
复制标题
具有动态不确定性的大规模非线性系统的模糊自适应分散输出反馈控制
DOI：
10.1109/tfuzz.2010.2050326
复制
发表时间：
2010-10
影响因子：
11.9
通讯作者：
Li, Yongming
中科院分区：
文献类型：
--
作者：
Tong, Shaocheng;Liu, Changliang;Li, Yongming
针对一类具有不可测状态的严格反馈非线性大系统，提出了一种自适应模糊分散鲁棒输出反馈控制方法。本文中的大规模非线性系统假设具有非结构不确定性、未建模动态和未知的高频增益符号。采用模糊逻辑系统逼近非结构化不确定性，设计K滤波器估计未测状态，引入动态信号和特殊Nussbaum增益函数分别解决高频增益符号未知和未建模不确定性占主导的问题。基于反推设计和自适应模糊控制方法，提出了一种自适应模糊分散鲁棒输出反馈控制方案。证明了所提出的自适应模糊控制方法可以保证闭环系统中所有信号一致最终有界，并且跟踪误差收敛到原点的一个小邻域。仿真结果表明了该方法的有效性。
In this paper, an adaptive fuzzy-decentralized robust output-feedback-control approach is proposed for a class of large-scale strict-feedback nonlinear systems with the unmeasured states. The large-scale nonlinear systems in this paper are assumed to possess the unstructured uncertainties, unmodeled dynamics, and unknown high-frequency-gain sign. Fuzzy-logic systems are used to approximate the unstructured uncertainties, K-filters are designed to estimate the unmeasured states, and a dynamical signal and a special Nussbaum gain function are introduced into the control design to solve the problem of unknown high-frequency-gain sign and dominate unmodeled uncertainties, respectively. Based on the backstepping design and adaptive fuzzy-control methods, an adaptive fuzzy-decentralized robust output-feedback-control scheme is developed. It is proved that the proposed adaptive fuzzy-control approach can guarantee that all the signals in the closed-loop system are uniformly and ultimately bounded, and the tracking errors converge to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by using simulation results.
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DOI：
10.1016/s0005-1098(97)00076-9
发表时间：
1997-09
期刊：
Autom.
影响因子：
--
作者：
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通讯作者：
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DOI：
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发表时间：
2000-11
期刊：
IEEE Trans. Autom. Control.
影响因子：
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作者：
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通讯作者：
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发表时间：
1998-11
期刊：
IEEE Trans. Autom. Control.
影响因子：
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作者：
X. Ye;Jingping Jiang
通讯作者：
X. Ye;Jingping Jiang
DOI：
10.1109/cdc.1992.371494
发表时间：
1992-12
期刊：
[1992] Proceedings of the 31st IEEE Conference on Decision and Control
影响因子：
--
作者：
A. Datta
通讯作者：
A. Datta
影响因子：
6.8
作者：
Jing Zhou;C. Wen
通讯作者：
Jing Zhou;C. Wen