A min-max model predictive control for a class of hybrid dynamical systems

This paper presents a min-max model predictive control algorithm for a class of hybrid systems by exploiting the equivalence between piecewise linear systems and mixed logical dynamical systems. The control algorithm consists of two control modes which are a state feedback mode and a min-max model p...

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Bibliographic Details
Published inProceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694) Vol. 2; pp. 694 - 699 vol.2
Main Authors Mukai, M., Kojima, A., Azuma, T., Fujita, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Control system synthesis
Control systems
Convergence
Piecewise linear techniques
Prediction algorithms
Predictive control
Predictive models
Remotely operated vehicles
State feedback
Systems engineering and theory
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Summary:This paper presents a min-max model predictive control algorithm for a class of hybrid systems by exploiting the equivalence between piecewise linear systems and mixed logical dynamical systems. The control algorithm consists of two control modes which are a state feedback mode and a min-max model predictive control mode. In the min-max model predictive control mode, the constrained positively invariant sets are used as the end set constraint, and an approach based on a min-max model predictive control formulation is employed. This control algorithm guarantees that the state converges to a union of constrained positively invariant sets with no constraint violation.
ISBN:9780780378667
0780378660
DOI:10.1109/CIRA.2003.1222265