An Iterative ADP Method to Solve for a Class of Nonlinear Zero-Sum Differential Games
In this chapter, an iterative ADP method is presented to solve a class of continuous-time nonlinear two-person zero-sum differential games. The idea is to use ADP technique to obtain the optimal control pair iteratively which makes the performance index function reach the saddle point of the zero-sum differential games. When the saddle point does not exist, the mixed optimal control pair is obtained to make the performance index function reach the mixed optimum. Rigid proofs are proposed to guarantee the control pair stabilize the nonlinear system. And the convergent property of the performance index function is also proved. Neural networks are used to approximate the performance index function, compute the optimal control policy and model the nonlinear system respectively for facilitating the implementation of the iterative ADP method. Two examples are given to demonstrate the validity of the proposed method.
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