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非线性耦合系统的分散自适应模糊控制 被引量:1

Decentralized adaptive fuzzy control of interconnected nonlinear systems
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摘要 针对一类具有高阶耦合作用的MIMO非线性系统 ,根据滑模控制原理 ,并利用模糊逻辑系统的逼近能力 ,提出一种分散自适应模糊控制器设计的新方案 .对每一个子系统 ,仅通过子系统的局部信息在线调节模糊系统的可调参数、滑模控制增益 ,从而实现了对动态不确定性及建模误差进行自适应补偿 .理论分析证明了闭环系统是全局稳定的 ,跟踪误差收敛到零的一个邻域内 . A new design scheme of decentralized adaptive fuzzy controller for a class of MIMO nonlinear systems with the high order interconnections is proposed in this paper. The design is based on the principle of sliding mode control and the approximation capability of fuzzy logic systems. The plant dynamic uncertainty and modeling errors are adaptively compensated by adjusted the parameters and sliding mode gains on line for each subsystem using only local information. By theoretical analysis, the closed loop fuzzy control system is proven to be globally stable, with tracking errors converging to a neighborhood of zero. Simulation results demonstrate the effectiveness of the approach.
出处 《东南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2003年第z1期31-35,共5页 Journal of Southeast University:Natural Science Edition
基金 国家自然科学基金资助项目 ( 60 0 740 13 ) 扬州大学信息科学学科群资助项目 (ISG0 3 0 60 6)
关键词 耦合系统 模糊控制 分散控制 自适应控制 全局稳定性 interconnected systems fuzzy control decentralized control adaptive control global stability
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参考文献7

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同被引文献8

  • 1张天平,梅建东,沈启坤.非线性系统的积分变结构间接自适应模糊控制[J].东南大学学报(自然科学版),2004,34(B11):5-10. 被引量:2
  • 2Wang L X.Stable adaptive fuzzy control of nonlinear systems[J].IEEE Trans on Fuzzy Systems,1993,1 (2):146-155.
  • 3Sanner R M,Slotine J J E.Gaussian networks for direct adaptive control[J].IEEE Trans on Neural Networks,1992,3(6):837-863.
  • 4Chen S C,Chen W L.Adaptive radial basis function neural network control with variable variance parameters[J].International Journal of Systems Science,2001,32(4):413-424.
  • 5Lee C Y,Lee J J.Adaptive control for uncertain nonlinear systems based on multiple neural networks[J].IEEE Trans on SMC,2004,34(1):325-333.
  • 6Lin C M,Peng Y F.Adaptive CMA C-based supervisory control for uncertain nonlinear systems[J].IEEE Trans on SMC,2004,34(2):1248-1260.
  • 7Hung C P.Integral variable structure control of nonlinear system using a CMAC neural networks learning approach[J].IEEE Trans on SMC,2004,34(1):702-709.
  • 8Chen C T,Peng S T.Learning control of process systems with hard input constraints[J].J Process Contr,1999,9(2):151-160.

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