Distributed Optimal Resource Allocation for High-Order Nonlinear Multiagent Systems Over Unbalanced Digraphs

IF 5 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Control of Network Systems Pub Date : 2024-07-23 DOI:10.1109/TCNS.2024.3432817
Zeli Zhao;Jinliang Ding;Jin-Xi Zhang;Yang Shi;Tianyou Chai
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Abstract

In this article, we consider the distributed optimal resource allocation problem with multiple coupled equality constraints for strict-feedback multiagent systems (MASs) over unbalanced digraphs. To solve this problem, a novel integrated distributed control strategy consisting of a set of optimal reference generators and a group of tracking controllers is proposed. The reference generator is based on the estimation of the left eigenvector of the Laplacian matrix and is suitable for unbalanced digraphs. Moreover, the backstepping design technique is efficiently combined with the distributed optimization scheme, leading to a systematic solution for the high-order nonlinear MAS. It is proven that all the outputs of the MAS exponentially converge to the optimal solution of the resource allocation problem under the proposed control. Compared with the existing optimal resource allocation strategies for MASs, the proposed control strategy is applicable to high-order nonlinear MASs and shows favorable exponential convergence, even for unbalanced digraphs. Finally, the simulation results illustrate the above-mentioned theoretical findings.
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非平衡数图上高阶非线性多代理系统的分布式最优资源分配
研究了不平衡有向图上严格反馈多智能体系统(MASs)具有多重耦合等式约束的分布式最优资源分配问题。为了解决这一问题,提出了一种由一组最优参考发生器和一组跟踪控制器组成的新型集成分布式控制策略。参考发生器基于拉普拉斯矩阵左特征向量的估计,适用于不平衡有向图。此外,将反演设计技术与分布式优化方案有效地结合起来,实现了高阶非线性MAS的系统求解。证明了在该控制下,MAS的所有输出都指数收敛于资源分配问题的最优解。与已有的质量最优资源分配策略相比,所提出的控制策略适用于高阶非线性质量,即使对于不平衡有向图也具有良好的指数收敛性。最后,仿真结果验证了上述理论结论。
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来源期刊
IEEE Transactions on Control of Network Systems
IEEE Transactions on Control of Network Systems Mathematics-Control and Optimization
CiteScore
7.80
自引率
7.10%
发文量
169
期刊介绍: The IEEE Transactions on Control of Network Systems is committed to the timely publication of high-impact papers at the intersection of control systems and network science. In particular, the journal addresses research on the analysis, design and implementation of networked control systems, as well as control over networks. Relevant work includes the full spectrum from basic research on control systems to the design of engineering solutions for automatic control of, and over, networks. The topics covered by this journal include: Coordinated control and estimation over networks, Control and computation over sensor networks, Control under communication constraints, Control and performance analysis issues that arise in the dynamics of networks used in application areas such as communications, computers, transportation, manufacturing, Web ranking and aggregation, social networks, biology, power systems, economics, Synchronization of activities across a controlled network, Stability analysis of controlled networks, Analysis of networks as hybrid dynamical systems.
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