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

HU Hui; LIU Guo-rong; GUO Peng; WANG Can

Volume 38 Issue 4

Aug. 2009

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INFORMATION AND CONTROL > 2009 > 38(4): 468-472,483.

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.

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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

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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.
- non-affine nonlinear,
- H_∞ tracking,
- neural network,
- observer

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