Constraint-Admissible Set for Linear Discrete-time System with Chance Constraints
نویسندگان
چکیده
Constraint-admissible sets have been widely used in the study of control of systems with hard constraints. This paper proposes a generalization of the maximal constraint admissible set for constrained linear discrete time system to the case where chance or probabilistic constraints are present. Defined in the most obvious way, the maximal probabilistic constraint-admissible set is not invariant. An inner approximation to it is then proposed which is invariant and has other nice properties. The application of this approximate set in a model predictive control framework where probabilistic constraints are present is discussed, including the feasibility and stability of the resultant closed-loop system. The effectiveness of the proposed approach is illustrated via numerical examples.
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