Optimal finite-horizon tracking control in affine nonlinear systems: A Stackelberg game approach with H2/H∞ framework

IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Applied Mathematics and Computation Pub Date : 2025-06-15 Epub Date: 2025-02-04 DOI:10.1016/j.amc.2025.129276
Xu Dong , Huaguang Zhang , Zhongyang Ming , Yanhong Luo
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Abstract

In this paper, we address the finite-time optimal tracking control problem within the context of a Stackelberg game structure, characterized by the mixed H2/H framework. This objective is accomplished through the innovative design and implementation of a novel Adaptive Dynamic Programming (ADP) algorithm. Initially, we establish a time-varying coupled Hamilton-Jacobi-Isaacs (HJI) equations, posing a significant challenge in deriving an analytical solution for the optimal leader. Subsequently, we elucidate the existence of Nash equilibrium points, confirming the algorithm's convergence and providing theoretical foundations for its practical application. Furthermore, we introduce a novel ADP algorithm that incorporates time-varying activation functions. The use of the Lyapunov direct method ensures the stability of the closed-loop affine nonlinear system under the ADP control scheme, thereby guaranteeing the system's uniformly ultimately bounded (UUB). Finally, the effectiveness of the aforementioned ADP-based control approach is validated through numerical simulations.
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仿射非线性系统的最优有限视界跟踪控制:H2/H∞框架下的Stackelberg对策方法
在本文中,我们研究了具有混合H2/H∞框架的Stackelberg博弈结构下的有限时间最优跟踪控制问题。这一目标是通过一种新的自适应动态规划(ADP)算法的创新设计和实现来实现的。首先,我们建立了一个时变耦合的Hamilton-Jacobi-Isaacs (HJI)方程,这对推导最优领导者的解析解提出了重大挑战。随后,我们阐明了纳什平衡点的存在性,证实了算法的收敛性,为其实际应用提供了理论基础。此外,我们还引入了一种包含时变激活函数的ADP算法。Lyapunov直接方法的使用保证了闭环仿射非线性系统在ADP控制方案下的稳定性,从而保证了系统的一致最终有界(UUB)。最后,通过数值仿真验证了上述基于adp的控制方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
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