Towards Redundant Constraint Removal in Scenario Approximation of Optimal Control Problems with Multiplicative Model Uncertainty
HA Nasir, E Weyer, I Shames, M Cantoni
2019 IEEE 58th Conference on Decision and Control (CDC) | IEEE | Published : 2020
Randomised approaches, such as the scenario approach, are employed to approximately solve robust optimisation problems with possibly infinite number of convex constraints. The idea is to solve the optimisation problem with a finite number of constraints randomly drawn from the original set of constraints. Precise results bounding how many constraints need to be drawn in order for the approximate problem solution to be a feasible solution for the original problem, with a given probability, are provided by the scenario theory. However, the number of constraints in the scenario problem can be large when there are many optimisation variables and the required probability of feasibility for the or..View full abstract
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Awarded by Australian Research Council
This work is supported by the Australian Research Council Linkage Project (LP130100605).