Adaptive multi-player pursuit–evasion games with unknown general quadratic objectives. (December 2022) - Cheng, Lei; Yuan, Yuan
Abstract: In this paper, an adaptive parameter estimation scheme is investigated for a class of multi-player pursuit–evasion games subject to unknown objectives with linear feedback and cross terms in control strategy. In virtue of the adaptive method, each player updates controller strategies to estimate opponent's control parameters before getting the Nash equilibrium solution. Moreover, the sufficient condition is provided to guarantee stability of the proposed adaptive procedure. Meanwhile, the stability behavior of closed-loop Nash strategy with adaptive estimator is guaranteed by the contraction mapping method. Finally, a simulation of an all-against-one game with one escaper and three pursuers is carried out to demonstrate the effectiveness of the proposed methodology. Highlights: Adaptive parameter estimators are designed for both sides of pursuers and escapers. The sufficient condition is provided to guarantee the convergence of the estimators. Sufficient conditions are obtained to stabilize the closed-loop system under Nash equilibrium solution.