Neural Network H ∞ Tracking Control of Nonlinear Systems Using GHJI Method

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 L2-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.

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