Closed-loop Identification for Control of Linear Parameter Varying Systems

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 Hansen 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 Hansen Scheme setups in simulation studies, and the application of the Hansen Scheme is seen to improve the identification performance.