Decentralized Adaptive Control of Large-Scale Nonaffine Nonlinear Systems Using Radial Basis Function Neural Networks(Systems Theory and Control,<Special Section>Nonlinear Theory and its Applications)

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概要

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• In this paper, a novel decentralized adaptive neural network controller is proposed for a class of large-scale nonlinear systems with unknown nonlinear, nonaffine subsystems and unknown nonlinear interconnections. The stability of the closed loop system is guaranteed by introducing a robust adaptive bound based on Lyapunov stability analysis. A radial-basis function type neural network is used in the paper. To show the effectiveness of the proposed method, we performed some simulation studies. The results of simulation become very promising.

• 社団法人電子情報通信学会の論文
• 2007-10-01

著者

• Karimi Bahram

  Electrical Engineering Department Amirkabir University Of Technology

• Menhaj Mohammad

  Amirkabir Univ. Of Technol. Tehran Irn

• Menhaj Mohammad

  Electrical Engineering Department Amirkabir University Of Technology

• SABOORI Iman

  Electrical Engineering Department, Amirkabir University of Technology

• Saboori Iman

  Electrical Engineering Department Amirkabir University Of Technology

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• Decentralized Adaptive Control of Large-Scale Nonaffine Nonlinear Systems Using Radial Basis Function Neural Networks(Systems Theory and Control,Nonlinear Theory and its Applications)
• A Novel Robust Impulsive Chaos Synchronization Approach for Uncertain Complex Dynamical Networks
• A Distributed Variational Bayesian Algorithm for Density Estimation in Sensor Networks

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