Distributed Optimal Coordination for Heterogeneous Linear Multiagent Systems

被引:66
作者
An, Liwei [1 ]
Yang, Guang-Hong [1 ,2 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Distributed optimization (DO); linear systems; multiagent networks; TIME CONVEX-OPTIMIZATION; CONSENSUS; ALGORITHMS; SENSOR;
D O I
10.1109/TAC.2021.3133269
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article studies the problem of distributed optimal coordination (DOC) for heterogeneous linear multiagent systems. Compared with the existing results where the structure constraints on local gradients or system matrices are required, the considered DOC framework is sufficiently general in the sense that no extra assumption is required except for the convexity/differentiability of local objective functions and the controllability/observability of linear systems. A necessary and sufficient condition for the existence of the solution to the DOC problem is derived in terms of the relationship between the objective function and so-called steady-state reachable set of linear systems. Under this fundamental condition, the original DOC problem is transformed into the one with additive equality constraint, without loss of the optimality, which generates a trackable solution for agent dynamics. By using a new state transformation technique, it is proved that the proposed DOC algorithm guarantees the global asymptotical convergence by utilizing only local interaction. Simulation results on the motion coordination illustrate the proposed algorithm.
引用
收藏
页码:6850 / 6857
页数:8
相关论文
共 38 条
[1]   Improved adaptive resilient control against sensor and actuator attacks [J].
An, Liwei ;
Yang, Guang-Hong .
INFORMATION SCIENCES, 2018, 423 :145-156
[2]   Equivalent Relaxations of Optimal Power Flow [J].
Bose, Subhonmesh ;
Low, Steven H. ;
Teeraratkul, Thanchanok ;
Hassibi, Babak .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2015, 60 (03) :729-742
[3]  
Briñón-Arranz L, 2013, 2013 EUROPEAN CONTROL CONFERENCE (ECC), P2831
[4]   Distributed Optimal Power Flow for Smart Microgrids [J].
Dall'Anese, Emiliano ;
Zhu, Hao ;
Giannakis, Georgios B. .
IEEE TRANSACTIONS ON SMART GRID, 2013, 4 (03) :1464-1475
[5]   Nash Equilibrium Seeking in Noncooperative Games [J].
Frihauf, Paul ;
Krstic, Miroslav ;
Basar, Tamer .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2012, 57 (05) :1192-1207
[6]   Distributed Continuous-Time Convex Optimization on Weight-Balanced Digraphs [J].
Gharesifard, Bahman ;
Cortes, Jorge .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2014, 59 (03) :781-786
[7]  
Greg Droge H. K., 2014, Journal of Control and Decision, V1, P191, DOI [10.1080/23307706.2014.926622, DOI 10.1080/23307706.2014.926622]
[8]   Hierarchical Optimal Power Flow Control for Loss Minimization in Hybrid Multi-terminal HVDC Transmission System [J].
Han, Minxiao ;
Xu, Dong ;
Wan, Lei .
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2016, 2 (01) :40-46
[9]  
Jing Wang, 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), P557, DOI 10.1109/ALLERTON.2010.5706956
[10]   Subgradient Methods and Consensus Algorithms for Solving Convex Optimization Problems [J].
Johansson, Bjorn ;
Keviczky, Tamas ;
Johansson, Mikael ;
Johansson, Karl Henrik .
47TH IEEE CONFERENCE ON DECISION AND CONTROL, 2008 (CDC 2008), 2008, :4185-4190