Authors:
Sorin Olaru
and
Didier Dumur
Affiliation:
Supelec – Automatic Control Department, France
Keyword(s):
Generalized Predictive Control, Feasibility, Polyhedral Representation, Parametric Programming.
Related
Ontology
Subjects/Areas/Topics:
Adaptive Signal Processing and Control
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
This paper analyzes the feasibility of the generalized predictive control law under constraints on the input,
output or other auxiliary signals that depend linearly on the system variables. These constraints are
formulated as sets of linear equalities or inequalities; the control sequence is therefore elaborated based on a quadratic optimization problem. The feasibility issues are related on one hand to the well posedness feature, and on the other hand to the compatibility with the set-point constraints. The prediction of the feasibility is of great interest from this point of view and necessary feasibility conditions are presented. Two possible approaches are followed, one strictly related to the specific set-point and the second, more general, examines the geo-metrical description of the optimization domain. The main practical advantage is that all the results are based on off-line numerical procedures offering qualitative information prior to the effective implementation.