14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper ThB1.4

Barenthin, Märta (KTH), Enqvist, Martin (Linköpings Univ.), Wahlberg, Bo (Royal Inst. of Tech. (KTH)), Hjalmarsson, Håkan (KTH)

Gain Estimation for Hammerstein Systems

Scheduled for presentation during the Invited Session "Nonlinear System Identification II" (ThB1), Thursday, March 30, 2006, 16:30−16:50, Concert Hall

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 22, 2018

Keywords Input and Excitation Design, Model Validation, Nonlinear System Identification


In this paper, we discuss and compare three different approaches for L2-gain estimation of Hammerstein systems. The objective is to find the input signal that maximizes the gain. A fundamental difference between two of the approaches is the class, or structure, of the input signals. The first approach involves describing functions and therefore the class of input signals is sinusoids. In this case we assume that we have a model of the system and we search for the amplitude and frequency that give the largest gain. In the second approach, no structure on the input signal is assumed in advance and the system does not have to be modelled first. The maximizing input is found using an iterative procedure called power iterations. In the last approach, a new iterative procedure tailored for memoryless nonlinearities is used to find the maximizing input for the unmodelled nonlinear part of the Hammerstein system. The approaches are illustrated by numerical examples.