Authors:
Hammoud Saari
1
and
Bernard Caron
2
Affiliations:
1
Ecole Nationale Supérieure Maritime, Algeria
;
2
Université de Savoie, France
Keyword(s):
Repetitive Control, Multivariable Systems, Invertible Systems, Non Invertible Systems, Tracking.
Related
Ontology
Subjects/Areas/Topics:
Control and Supervision Systems
;
Hybrid Learning Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Components for Control
;
Intelligent Control Systems and Optimization
;
Machine Learning in Control Applications
;
Optimization Algorithms
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
This paper deals with an iterative learning control law for multivariable systems. The desired inputs are supposed to be known and periodic. The principle of the control is to make outputs as close as possible to desired inputs at each new period. After the design of multivariable repetitive controller, we give the stability condition of the algorithm and some simulation results.