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Event-Triggered Adaptive Dynamic Programming for Non-Zero-Sum Games of Unknown Nonlinear Systems via Generalized Fuzzy Hyperbolic Models

机译:基于广义模糊双曲模型的未知非线性系统非零和博弈的事件触发自适应动态规划

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摘要

In this paper, by incorporating the event-triggered mechanism and the adaptive dynamic programming algorithm, a novel near-optimal control scheme for a class of unknown nonlinear continuous-time non-zero-sum (NZS) differential games is investigated. First, a generalized fuzzy hyperbolic model based identifier is established, using only the input-output data, to relax the requirement for the complete system dynamics. Then, under the event-based framework, the coupled Hamilton-Jacobi equations are derived for the multiplayer NZS games. Then, the adaptive critic design method is employed to approximate the optimal control policies; thus, an identifier-critic architecture is developed to obtain the event-triggered controller. By the virtue of the Lyapunov theory, a state-dependent triggering condition, which is different from the existing works, is developed to achieve the stability of the closed-loop control system both for the continuous and jump dynamics. Finally, two numerical examples are simulated to substantiate the feasibility of the analytical design.
机译:本文通过结合事件触发机制和自适应动态规划算法,研究了一类未知的非线性连续时间非零和(NZS)差分博弈的新型最优控制方案。首先,仅使用输入-输出数据建立基于广义模糊双曲模型的标识符,以放松对完整系统动力学的要求。然后,在基于事件的框架下,为多人NZS游戏导出了耦合的Hamilton-Jacobi方程。然后,采用自适应批评家设计方法对最优控制策略进行近似。因此,开发了一种识别标识符的体系结构来获取事件触发的控制器。借助李雅普诺夫理论,开发了一种状态依赖的触发条件,该条件不同于现有的工作条件,以实现闭环控制系统在连续和跳跃动力学方面的稳定性。最后,模拟了两个数值示例,以证实分析设计的可行性。

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