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Optimal, Robust Predictive Control of Nonlinear Systems under Probabilistic Uncertainty using Particles

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2 Author(s)
Blackmore, L. ; Massachusetts Inst. of Technol., Cambridge ; Williams, B.C.

In this paper we present a novel method for robust, optimal control of nonlinear systems under probabilistic uncertainty. The method extends a previous approach for linear systems that approximates the distribution of the predicted system state using a finite number of particles. We couple this particle-based approach with a nonlinear solver that does not take into account uncertainty to give a new method for nonlinear, robust control. Any solution returned by the algorithm is guaranteed to be e-close to a local optimum of the nonlinear stochastic control problem.

Published in:

American Control Conference, 2007. ACC '07

Date of Conference:

9-13 July 2007