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Closed‐Loop Identification for Control of Linear Parameter Varying Systems
Author(s) -
Bendtsen Jan,
Trangbaek Klaus
Publication year - 2014
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.612
Subject(s) - control theory (sociology) , identification (biology) , identification scheme , controller (irrigation) , linear system , system identification , affine transformation , scheme (mathematics) , lti system theory , computer science , closed loop , dependency (uml) , open loop controller , control system , control engineering , mathematics , control (management) , engineering , artificial intelligence , data modeling , data mining , mathematical analysis , botany , electrical engineering , database , pure mathematics , agronomy , biology , measure (data warehouse)
This paper deals with system identification for control of linear parameter varying systems. In practical applications, it is often important to be able to identify small plant changes in an incremental manner without shutting down the system and/or disconnecting the controller; unfortunately, closed‐loop system identification is more difficult than open‐loop identification. In this paper we prove that the so‐called H ansen scheme, a technique known from linear time‐invariant systems theory for transforming closed‐loop system identification problems into open‐loop‐like problems, can be extended to accommodate linear parameter varying systems as well. We investigate the identified subsystem's parameter dependency and observe that, under mild assumptions, the identified subsystem is affine in the parameter vector. Various identification methods are compared in direct and H ansen Scheme setups in simulation studies, and the application of the Hansen Scheme is seen to improve the identification performance.