Internal-Model-Based Design of Repetitive and Iterative Learning Controllers for Linear Multivariable Systems DICK DE ROOVER SC Solutions Inc. 3211 Scott Boulevard Santa Clara, CA 95054 USA roover@scsolutions.com OKKO H. BOSGRA Mechanical Engineering Systems and Control Group Delft University of Technology Mekelweg 2, 2628 CD Delft The Netherlands o.h.bosgra@wbmt.tudelft.nl MAARTEN STEINBUCH Faculty of Mechanical Engineering, Systems and Control Group Eindhoven University of Technology P.O. Box 513, 5600 MB Eindhoven The Netherlands m.steinbuch@wfw.wtb.tue.nl Abstract Repetitive and iterative learning control are two modern control strategies for tracking systems in which the signals are periodic in nature. This paper discusses repetitive and iterative learning control from an internal model principle point of view. This allows the formulation of existence conditions for multivariable implementations of repetitive and learning control. It is shown that repetitive control can be realized by an implementation of a robust servomechanism controller that uses the appropriate internal model for periodic disturbances. The design of such controllers is discussed. Next it is shown that iterative learning control can be implemented in the format of a disturbance observer/compensator. It is shown that the resulting control stucture is dual to the repetitive controller, and that both constitute an implementation of the internal model principle. Consequently, the analysis and design of repetitive and iter- ative learning control can be generalized to the powerful analysis and design proce- dure of the internal model framework, allowing to trade-off the convergence speed for periodic-disturbance cancellation versus other control objectives, such as stochastic disturbance suppression. Author to whom correspondence should be addressed. Tel: 408.486.6060 Ext 34. Fax: 408.486.6083.