Optimal Output Synchronization of Euler–Lagrange Systems With Uncertain Time-Varying Quadratic Cost Functions

IF 10.5 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2025-02-19 DOI:10.1109/TCYB.2025.3537764
Liangze Jiang;Zheng-Guang Wu;Lei Wang;Yong Xu;Wei-Wei Che
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Abstract

In this article, we study the optimal output synchronization problem (OOSP) for uncertain networked Euler-Lagrange (EL) systems. Specifically, the system outputs are expected to be synchronized at the solution of an uncertain distributed time-varying quadratic optimization problem, where each local time-varying cost function includes uncertain parameters. From a centralized perspective, we first develop a controller with adaptive control gains to guide the output of a double-integrator system toward the time-varying optimal solution. By employing the modified average estimators, we extend the centralized design to a distributed implementation to address the OOSP for uncertain EL systems. Using matrix trace properties and composite Lyapunov analysis, we prove that the system outputs can asymptotically converge to the desired time-varying optimal solution. Two examples are used to verify the proposed designs.
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具有不确定时变二次代价函数的Euler-Lagrange系统的最优输出同步
本文研究了不确定网络欧拉-拉格朗日(EL)系统的最优输出同步问题。具体来说,系统输出在求解不确定的分布式时变二次优化问题时是同步的,其中每个局部时变代价函数都包含不确定参数。从集中的角度来看,我们首先开发了一个具有自适应控制增益的控制器,以引导双积分器系统的输出向时变最优解方向发展。通过使用改进的平均估计量,我们将集中设计扩展到分布式实现,以解决不确定EL系统的OOSP问题。利用矩阵迹迹性质和复合李雅普诺夫分析,证明了系统输出可以渐近收敛到期望的时变最优解。用两个实例验证了所提出的设计。
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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