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Volume 38 Issue 4
Aug.  2009
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HU Hui, LIU Guo-rong, GUO Peng, WANG Can. Observer-based Adaptive Neural-Network H∞ Tracking Control for a Class of Non-affine Nonlinear Systems[J]. INFORMATION AND CONTROL, 2009, 38(4): 468-472,483.
Citation: HU Hui, LIU Guo-rong, GUO Peng, WANG Can. Observer-based Adaptive Neural-Network H∞ Tracking Control for a Class of Non-affine Nonlinear Systems[J]. INFORMATION AND CONTROL, 2009, 38(4): 468-472,483.
shu

Observer-based Adaptive Neural-Network H∞ Tracking Control for a Class of Non-affine Nonlinear Systems

  • 1.

    College of Electrical and Information Engineering, Hunan University, Changsha 410082, China

  • 2.

    Hunan Institute of Engineering, Xiangtan 411101, China

  • 3.

    China Nuclear Power Engineering Co., LTD, Shenzhen 518028, China

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  • Received Date: September 15, 2008
  • Published Date: August 19, 2009
    Graphical Abstract
    • Abstract
  • An observer-based adaptive neural-network H∞ tracking control scheme is presented for a class of non-affine nonlinear systems with external disturbance and unavailable states.By using implicit function theorem,Taylor's formula and mean theorem,the form of the non-affine nonlinear systems is transformed into the form of affine nonlinear systems.The controller consists of an equivalent controller and H∞ controller designed to attenuate the effect of external disturbance and approximation errors of the neural networks on tracking.The overall control scheme and the weight update laws based on Lyapunov stability theory can guarantee the system stability and asymptotic convergence of the tracking error to zero,and attenuate the effect of the disturbance on system to a prescribed level.Theoretical analysis and simulation results demonstrate the effectiveness of the approach.
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    • References (9)
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