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Adaptive critic design for nonlinear multi-player zero-sum games with unknown dynamics and control constraints

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Abstract

In this paper, a novel optimal control scheme is established to solve the multi-player zero-sum game (ZSG) issue of continuous-time nonlinear systems with control constraints and unknown dynamics based on the adaptive critic technology. To relax the requirement of system dynamics, a neural network-based identifier is applied to reconstruct the unknown multi-player ZSG system. Then, by developing a new nonquadratic function, the associated Hamilton-Jacobi-Isaacs (HJI) equation of the constrained ZSG is derived. Moreover, an adaptive critic framework is constructed to approximate the optimal cost function. Meanwhile, the strategy sets of optimal control and the worst disturbance are estimated by utilizing the single-critic network, respectively. After that, a modified critic weight updating mechanism with experience replay technique is introduced to relax the requirement of the persistence of excitation condition. Theoretically, by employing the Lyapunov stability theorem, the uniform ultimate boundedness stability of the ZSG system state and the critic network weight approximation error are proved. Finally, a representative example is simulated to validate the efficacy of the constructed framework.

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Funding

This work was supported in part by the National Key Research and Development Program of China under Grant 2021ZD0112302; and in part by the National Natural Science Foundation of China under Grant 62222301, Grant 61890930-5, and Grant 62021003.

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Correspondence to Junfei Qiao.

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Huo, Y., Wang, D., Qiao, J. et al. Adaptive critic design for nonlinear multi-player zero-sum games with unknown dynamics and control constraints. Nonlinear Dyn 111, 11671–11683 (2023). https://doi.org/10.1007/s11071-023-08419-5

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