Identification of linear parameter-varying systems via IO and subspace identification - a comparison

Abstract

A common challenge associated with designing a Linear Parameter-Varying (LPV) controller for a nonlinear plant is identification of a plant model in state-space form with static parameter dependency. Till date, the two most frequently used methods to solve this problem are special canonical forms of Input-Output (IO) and subspace (SS) identification. This paper compares both identification methods on various criteria with a focus on low-complexity LPV systems. Features of both methods are illustrated by identification results on a simulated MIMO LPV system taken from the literature and by experimental results on the air-path system of a gasoline engine. Finally, some insight into the selection of an identification method for a given model class is provided.