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H_∞控制理论及应用的研究综述 被引量:7

The Research Actuality of H_∞ Control theory and its application
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摘要 H∞控制是一种具有很好鲁棒性的设计方法,具有设计思想明确、控制效果好等优点,尤其适用于模型摄动的多输入多输出(MIMO)系统。H∞控制在控制理论、设计方法及应用等方面,经过多年不断发展和完善,已成为一种具有较完整体系的鲁棒控制理论。为适应控制系统稳定性、自适应性、智能化及工程化的更高要求,基于线性矩阵不等式(LMI)的H∞控制、非线性H∞控制以及H∞控制与神经网络和模糊控制结合,成为近年来H∞控制研究的热点。随着H∞控制研究的深入,其存在的诸如理论复杂、计算量大和参数摄动范围有限等问题将会逐步得到解决,适用范围也会更广、应用前景会更好。 H∞ Control is a design method with good robustness and fine control effect, which is especially adaptive to Multi - Input Multi - Output (MIMO) system of model change. Now H∞ Control has become a systematic robust control theory in the aspects as control theory, design method and application. In order to be adaptive to higher demands of control system stability, self - adaptability, intelligentizing and engineering, the H∞ Control based on Linear Matrix Inequalities (LMI), the nonlinear H∞ Control and the H∞ Control combined with neural networks and fuzzy control have become hotspots of H∞ Control research in the recent years. With the development of H∞ Control research, the existed problems such as theory complexity, large calculation cost and limited parameter change scope will be solved step by step. It will find a wider and better application.
出处 《电光与控制》 北大核心 2007年第3期87-91,共5页 Electronics Optics & Control
基金 国防重点实验室资助项目 河南省高校青年骨干教师资助计划(2002[121])
关键词 H∞控制理论 MIMO系统 非线性H∞控制 LMI 时滞 不确定性 H∞ Control theory MIMO system nonlinear H∞ Control LMI time - delay uncertainty
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  • 1吴敏 桂卫华.现代鲁棒控制[M].长沙:中南工业大学出版社,1998..
  • 2顾永如.不确定系统的稳定性与鲁棒控制[M].杭州:浙江大学,1998..
  • 3Hunt K J, Sbarbaro D. Neural networks for nonlinear internal model control[J]. IEEE Proceedings D, 1991, 138(5) :431-438.
  • 4Park J, Sand Berg J W. Universal approximation using radial-basis-function networks [J]. Neural Computation,1991,3(2) : 246-257.
  • 5Chen S, Cowan C F N, Grant P M. Orthogonal least squares learning algorithm for radial basis function networks[J]. IEEE Trans Neural Networks, 1991,2 (2) : 302 - 309.
  • 6Sanner P, Slotine J J. Gaussian networks for direct adaptive control [J]. IEEE Transactions on Neural Networks 1992,3(6),837-864.
  • 7Liu C C, Chen F H. Adaptive control of nonlinear continuous systems using neural networks-general relation degree and MIMO cases[J], lnt J of Control, 1993, 58(2):317-335.
  • 8Tong S C, Tang J T, Wang T. Fuzzy adaptive control of muhivariable nonlinear systems [J]. Fury Sets and Systems,2000,11(1) ,163-167.
  • 9郭雷,忻欣,冯纯伯.鲁棒H^∞性能问题的分析和降阶输出反馈控制器设计[J].科学通报,1997,42(5):543-548. 被引量:2
  • 10Xie L,Proc IFAC’96,1996年,167页

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