Approximate-optimal control algorithm for constrained zero-sum differential games through event-triggering mechanism

This paper investigates the optimization problem of two-player zero-sum differential game with control constraints in the framework of event triggering. Relying on reinforcement learning, an adaptive dynamic programming algorithm is developed to approximate the optimal solution of zero-sum game, i.e...

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Veröffentlicht in:	Nonlinear dynamics Jg. 95; H. 4; S. 2639 - 2657
Hauptverfasser:	Mu, Chaoxu, Wang, Ke
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.03.2019 Springer Nature B.V
Schlagworte:	Adaptive algorithms Automotive Engineering Classical Mechanics Closed loops Communication Constraints Control Control algorithms Control theory Design Differential games Distance learning Dynamic programming Dynamical Systems Engineering Equilibrium Feedback control Game theory Machine learning Mathematical analysis Mechanical Engineering Neural networks Optimal control Optimization Original Paper Saddle points (game theory) Teaching methods Vibration Zero sum games Neural network (NN) Event triggering Zero-sum differential game Control constraints Adaptive dynamic programming (ADP)
ISSN:	0924-090X, 1573-269X
Online-Zugang:	Volltext
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