
doi: 10.1002/asjc.612
AbstractThis 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‐calledHansen 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 andHansen Scheme setups in simulation studies, and the application of the Hansen Scheme is seen to improve the identification performance.
closed-loop system identification, Closed-loop identification, Discrete-time control/observation systems, Linear systems in control theory, linear parameter varying systems, Minimal systems representations, Youla-Kucera parameterization, Feedback control, Linear parameter varying (LPV) control
closed-loop system identification, Closed-loop identification, Discrete-time control/observation systems, Linear systems in control theory, linear parameter varying systems, Minimal systems representations, Youla-Kucera parameterization, Feedback control, Linear parameter varying (LPV) control
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