Barrier Function Based Consensus of High-Order Nonlinear Multi-agent Systems with State Constraints

被引：3
|
作者：
Fu, Junjie [1 ]
Wen, Guanghui [1 ]
Lv, Yuezu [1 ]
Huang, Tingwen [2 ]
机构：
[1] Southeast Univ, Sch Math, Jiangsu Prov Key Lab Networked Collect Intelligen, Nanjing 211189, Peoples R China
[2] Texas A&M Univ Qatar, Doha, Qatar
来源：
NEURAL INFORMATION PROCESSING (ICONIP 2019), PT II | 2019年 / 11954卷
基金：
中国国家自然科学基金;
关键词：
Multi-agent system; Nonlinear systems; State constraints; Input saturation; Consensus; Barrier function; LEADER-FOLLOWING CONSENSUS; DOUBLE-INTEGRATOR DYNAMICS; INPUT SATURATION; LYAPUNOV FUNCTIONS; VELOCITY; ALGORITHMS; TRACKING;
D O I：
10.1007/978-3-030-36711-4_41
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Consensus control of a class of high-order nonlinear multi-agent systems subject to multiple state constraints and input saturation is studied in this work. Barrier functions are employed to design a distributed controller which achieves consensus without violating the state constraints and input saturation provided that some feasibility conditions on the initial states and controller parameters are satisfied. The feasibility conditions can be checked off-line. Backstepping method and Lyapunov analysis are employed to study the convergence properties of the designed controller.
引用
收藏
页码：492 / 503
页数：12
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