Distributed Output-Feedback Consensus Control of Multiagent Systems with Unknown Output Measurement Sensitivity

作     者：Li, Kuo Hua, Chang-Chun You, Xiu Guan, Xin-Ping 

作者机构：Yanshan Univ Inst Elect Engn Qinhuangdao 066004 Hebei Peoples R China Shanxi Univ Sch Math Sci Taiyuan 030006 Peoples R China Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China 

出 版 物：《IEEE TRANSACTIONS ON AUTOMATIC CONTROL》 (IEEE自动控制汇刊)

年 卷 期：2021年第66卷第7期

页      面：3303-3310页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0811[工学-控制科学与工程] 

基　　金：National Key R&D Program of China [2018YFB1308300] National Natural Science Foundation of China [61825304, 61751309, 61673335, 61803243] 

主　　题：Topology Output feedback Multi-agent systems Sensitivity Observers Consensus algorithm Heuristic algorithms Consensus control distributed observer K-filter multiagent systems unknown output measurement sensitivity 

摘      要：This article addresses the leader-following consensus problem for multiagent systems with unknown output measurement sensitivity based on a fixed directed topology. Different from the existing works on the consensus problem, the output measurement sensitivity is described as a total unknown parameter. Under this nonideal condition, we put forward a distributed output-feedback consensus control algorithm for the first time. To start with, we design the novel distributed high-gain observer and a high-gain K-filter for each follower, which are utilized to reconstruct the state of the leader and the follower, respectively. Subsequently, the consensus problem is transformed into the stability problem by introducing appropriate state transformation. By using the backstepping control method, the distributed output-feedback controller with an adaptive law is designed for each follower with the help of a Nussbaum-type function. Based on the Lyapunov stability theory, it is strictly proved that all agents can achieve a consensus with the designed controller. Finally, the numerical simulation is presented to illustrate the effectiveness of theoretical results.