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Zero-sum games-based adaptive tracking control for nonlinear systems of event-driven under asymmetric constraints via DHP
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DOI：10.1016/j.cnsns.2026.110512.png)
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Abstract
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• The tracking error system (TES) is established by using system state data and reference signals, and the OTC problem is transformed into the optimal regulation problem of the TES. The corresponding optimal H∞ tracking controller is derived within the ZSGs framework. • In order to avoid the adverse effects of asymmetric control constraints on the stable operation of the system. By introducing a novel non-quadratic function into the cost function, the problem of asymmetric actuator constraint is transformed into an unconstrained problem. • A novel DEDS scheme is designed based on input-to-state stability theory. This scheme aims to reduce the waste of network resources, ensure that the learning processes of the control and disturbance networks are mutually independent, and mitigate the coupled triggering phenomenon. • A new optimal H∞ tracking control algorithm with an actor-critic-disturbance-feedforward neural architecture is proposed. The incorporation of the feedforward neural controller further addresses the issue that the unknown dynamics of the NDTS were not rigorously considered. In addition, the DHP technique is employed to enhance the convergence speed of the algorithm and to preserve more comprehensive state information.
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