Open AccessEvent‐triggered scheduling for pinning networks of coupled dynamical systems under stochastically fast switching
Author(s) -
Han Yujuan,
Lu Wenlian,
Chen Tianping
Publication year - 2021
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/cth2.12151
Subject(s) - control theory (sociology) , coupling (piping) , scheduling (production processes) , computer science , coupling strength , stability (learning theory) , set (abstract data type) , topology (electrical circuits) , mathematics , physics , mathematical optimization , engineering , control (management) , artificial intelligence , mechanical engineering , combinatorics , machine learning , programming language , condensed matter physics
This paper studies the stability of linearly coupled dynamical systems with feedback pinning algorithms. Here, both the coupling matrix and the set of pinned‐nodes are time‐varying, induced by stochastic processes. Event‐triggered rules are employed in both diffusion coupling and feedback pinning terms, which can reduce the actuation and communication loads. Two event‐triggered rules are proposed and it is proved that if the system with time‐average couplings and pinning gains is stable and the switching of coupling matrices and pinned nodes is sufficiently fast, the proposed event‐triggered strategies can stabilize the system. Moreover, Zeno behaviour can be excluded for all nodes. Numerical examples of networks of mobile agents are presented to illustrate the theoretical results.