Open AccessAdaptive near‐optimal controllers for non‐linear decentralised feedback stabilisation problems
Author(s) -
Wang Ding,
He Haibo,
Zhao Bo,
Liu Derong
Publication year - 2017
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.2016.1383
Subject(s) - control theory (sociology) , computer science , stability (learning theory) , focus (optics) , adaptive control , optimal control , control engineering , property (philosophy) , decentralised system , control (management) , controller (irrigation) , feedback control , mathematical optimization , engineering , mathematics , artificial intelligence , agronomy , philosophy , physics , epistemology , machine learning , optics , biology
The authors focus on developing adaptive‐critic‐based near‐optimal controllers to solve continuous‐time non‐linear decentralised feedback stabilisation problems. The decentralised feedback control problem with respect to the matched interconnected systems is addressed by designing the optimal controllers of the corresponding isolated subsystems. By employing a novel updating rule to reduce the requirement about the initial stabilising control, the adaptive‐critic‐based near‐optimal feedback controllers can be obtained with an excellent approximation property. The closed‐loop form of each isolated subsystem is constructed and its stability is handled by incorporating the improved learning mechanism. A simulation example is also conducted to verify the decentralised control performance of the present approach.