scholarly journals Observer-Based Consensus Control for Heterogeneous Multi-Agent Systems with Output Saturations

2021 ◽  
Vol 11 (10) ◽  
pp. 4345
Author(s):  
Young-Hun Lim ◽  
Gwang-Seok Lee

This paper studies the consensus problem for heterogeneous multi-agent systems with output saturations. We consider the agents to have different dynamics and assume that the agents are neutrally stable and that the communication graph is undirected. The goal of this paper is to achieve the consensus for leaderless and leader-following cases. To solve this problem, we propose the observer-based distributed consensus algorithms, which consists of three parts: the nonlinear observer, the reference generator, and the regulator. Then, we analyze the consensus based on the Lasalle’s Invariance Principle and the input-to-state stability. Finally, we provide numerical examples to demonstrate the validity of the proposed algorithms.

2019 ◽  
Vol 356 (6) ◽  
pp. 3612-3627 ◽  
Author(s):  
Yuan Wang ◽  
Jianwei Xia ◽  
Zhen Wang ◽  
Jianping Zhou ◽  
Hao Shen

Author(s):  
Chengzhi Yuan

This paper addresses the problem of leader-following consensus control of general linear multi-agent systems (MASs) with diverse time-varying input delays under the integral quadratic constraint (IQC) framework. A novel exact-memory distributed output-feedback delay controller structure is proposed, which utilizes not only relative estimation state information from neighboring agents but also local real-time information of time delays and the associated dynamic IQC-induced states from the agent itself for feedback control. As a result, the distributed consensus problem can be decomposed into H∞ stabilization subproblems for a set of independent linear fractional transformation (LFT) systems, whose dimensions are equal to that of a single agent plant plus the associated local IQC dynamics. New delay control synthesis conditions for each subproblem are fully characterized as linear matrix inequalities (LMIs). A numerical example is used to demonstrate the proposed approach.


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