论文标题
部分可观测时空混沌系统的无模型预测
Closed-Loop Stackelberg Strategy for Linear-Quadratic Leader-Follower Game
论文作者
论文摘要
本文关注的是线性季度领导者追随者游戏的闭环Stackelberg策略。与开环和反馈stackelberg策略完全不同，即使是线性情况，闭环解决方案的解决性仍然具有挑战性。本文的主要贡献是在Riccati方程方面具有一步记忆的明确线性闭环Stackelberg策略。关键技术是将约束的最大原理应用于领导者追随者游戏，并明确求解相应的前进差方程。数值示例验证了结果的有效性，这比反馈策略更好。
This paper is concerned with the closed-loop Stackelberg strategy for linear-quadratic leader-follower game. Completely different from the open-loop and feedback Stackelberg strategy, the solvability of the closed-loop solution even the linear case remains challenging. The main contribution of the paper is to derive the explicitly linear closed-loop Stackelberg strategy with one-step memory in terms of Riccati equations. The key technique is to apply the constrained maximum principle to the leader-follower game and explicitly solve the corresponding forward and backward difference equations. Numerical examples verify the effectiveness of the results, which achieves better performance than feedback strategy.
