Open AccessDistributed adaptive control for a class of leader–following heterogeneous networks under intermittent communication environment
Author(s) -
Liu Heng,
Wang Xin,
Zhu JunWei,
Zhang Xian
Publication year - 2020
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2020.0055
Subject(s) - computer science , control theory (sociology) , adaptive control , multi agent system , controller (irrigation) , distributed computing , consensus , protocol (science) , network topology , estimator , decentralised system , lyapunov function , constraint (computer aided design) , topology (electrical circuits) , control engineering , control (management) , nonlinear system , engineering , mathematics , computer network , artificial intelligence , medicine , mechanical engineering , statistics , physics , alternative medicine , electrical engineering , pathology , quantum mechanics , agronomy , biology
This paper addresses the distributed adaptive tracking control problem for a class of multi‐agent systems under intermittent communication constraints, where the dynamics of each follower subsystem contain heterogeneous mismatched affine uncertainties. Although some distributed adaptive consensus protocols were developed in previous work, several potential limitations of adaptive consensus controller design are difficult to overcome when the switching communication topology contains asymmetrical architecture and discontinuous failures. To overcome the main obstacles, the authors propose a novel adaptive coordination control algorithm such that the follower subsystems are enabled to track the states of a leader. By using the neighbourhood information, a distributed estimator like‐protocol is constructed, under which, each subsystem can estimate the desire state information even under the intermittent connection constraint in directed switching topology. Then, in view of heterogeneous mismatched affine uncertainties, a decentralised adaptive controller with updating local parameters is presented to guarantee that each agent states track desire trajectories. Technically, by exploiting topology‐dependent multiple Lyapunov functions approach, S‐procedure technique and adaptive mechanism, the synchronisation conditions of the adaptive consensus algorithm are established to prove the synchronisation of heterogeneous agents even in the presence of intermittent communication failures. Finally, an example demonstrates the effectiveness for the proposed method.