On the Benefit of Re-optimization in Optimal Control under Perturbations
Abstract
We consider a finite-horizon optimal control problem for a system subject to perturbations. We compare the performance of the nominal optimal control sequence under perturbations with a shrinking horizon strategy in which a re-optimization for the nominal model is performed in each sampling instant using the current perturbed system state as new initial value. We analyze the potential performance improvement using suitable moduli of continuity as well as stability and controllability properties and illustrate our findings by numerical simulations.
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