期刊
AUTOMATICA
卷 78, 期 -, 页码 123-134出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2016.12.016
关键词
Control system analysis; Controllability; Structural properties; Graph theory; Combinatorial mathematics
资金
- Fundacao para a Ciencia e a Tecnologia (FCT) [SFRH/BD/33779/2009]
- CMU-Portugal (ICTI) program
- FEDER funds through COMPETE [NSF CIF-1513936, POCI-01-0145-FEDER-006933/SYSTEC]
- FCT
- Knut and Alice Wallenberg Foundation
- Swedish Strategic Research Foundation
- Swedish Research Council
- Fundação para a Ciência e a Tecnologia [SFRH/BD/33779/2009] Funding Source: FCT
Motivated by the development and deployment of large-scale dynamical systems, often comprised of geographically distributed smaller subsystems, we address the problem of verifying their controllability in a distributed manner. Specifically, we study controllability in the structural system theoretic sense, structural controllability, in which rather than focusing on a specific numerical system realization, we provide guarantees for equivalence classes of linear time-invariant systems on the basis of their structural sparsity patterns, i.e., the location of zero/nonzero entries in the plant matrices. Towards this goal, we first provide several necessary and/or sufficient conditions that ensure that the overall system is structurally controllable on the basis of the subsystems' structural pattern and their interconnections. The proposed verification criteria are shown to be efficiently implementable (i.e., with polynomial time complexity in the number of the state variables and inputs) in two important subclasses of interconnected dynamical systems: similar (where every subsystem has the same structure) and serial (where every subsystem outputs to at most one other subsystem). Secondly, we provide an iterative distributed algorithm to verify structural controllability for general interconnected dynamical system, i.e., it is based on communication among (physically) interconnected subsystems, and requires only local model and interconnection knowledge at each subsystem. (C) 2016 Elsevier Ltd. All rights reserved.
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