Iterative learning control of nonlinear non-minimum phase systems and its application to system and model inversion

• In this contribution we present a model based method for reference tracking in the Iterative Learning Control (ILC) framework. The method can be applied to nonlinear, possibly non-minimum phase, systems. The idea is to use the inverse of a linearized model in the ILC update. In the non-minimum phase case, the batch property of ILC is explored by means of non-causal filtering. Apart from reference tracking, this method is useful for system and model inversion - a problem that arises in many disciplines where nonlinear systems and models are involved, e.g. maximum likelihood identification and input design for identification for control. The method is illustrated on a numerical example.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)

Keyword

Automation & Control Systems

Electrical & Electronic

Automatic control

Reglerteknik

SRA - ICT

SRA - Informations- och kommunikationsteknik

TECHNOLOGY

Publication and Content Type

ref (subject category)

kon (subject category)