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A state-space implementation of anti-causal iterative learning control

: Becker, U.; Damm, T.


Proceedings in applied mathematics and mechanics. PAMM 10 (2010), Nr.1, S.599-600
ISSN: 1617-7061
Gesellschaft für Angewandte Mathematik und Mechanik GAMM (Jahrestagung) <81, 2010, Karlsruhe>
Zeitschriftenaufsatz, Konferenzbeitrag
Fraunhofer ITWM ()

Iterative learning control is used to find input signals which match a previously generated output trajectory by repetitively correcting the inputs through the tracking errors. Using causal learning operators this only works up to a relative degree of one. We overcome this restriction with an anti-causal approach following [1] and show a practical implementation in the state-space with some examples. We also motivate the method as useful to determine inputs for simulations and test-rigs.