Iterative Learning Control of Nonlinear Non-Minimum Phase Systems and its Application to System and Model Inversion

• In this contribution we place ILC in the realm of numerical optimization. This clarifies the role played by the design variables and how they affect e.g. convergence properties. We give a model based interpretation of these design variables and also a sufficient condition for convergence of ILC which is similar in spirit to the sufficient and necessary condition previously derived for linear systems. This condition shows that the desired performance has to be traded against modelling accuracy. Finally, one of the main benefits of ILC when non-minimum phase systems are concerned, the possibility of non-causal control, is given a comprehensive coverage.

Ämnesord

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

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

Nyckelord

Iterative methods

learning control

nonlinear systems

convergence analysis

non-minimum phase systems

Automatic control

Reglerteknik

Publikations- och innehållstyp

vet (ämneskategori)

rap (ämneskategori)