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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Neural Network H ∞ Tracking Control of Nonlinear Systems Using GHJI Method
verfasst von : Derong Liu, Yuzhu Huang, Qinglai Wei
Erschienen in: Advances in Neural Networks – ISNN 2013
Verlag: Springer Berlin Heidelberg
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In this paper, an
H
∞
optimal tracking control scheme based on generalized Hamilton-Jacobi-Isaacs (GHJI) equation is developed for discrete-time (DT) affine nonlinear systems. First, via system transformation, the optimal tracking problem is transformed into an optimal regulation problem with respect to the state tracking error. Second, with regard to the converted regulation problem, in order to obtain the
H
∞
tracking control, the corresponding GHJI equation is formulated, and then the
L
2
-gain analysis of the closed-loop nonlinear system are employed. Third, an iterative algorithm based on the GHJI equation by using neural networks (NNs) is introduced to solve the optimal control. Finally, simulation results are presented to demonstrate the effectiveness of the proposed scheme.