Stochastic linear model predictive control using nested decomposition
Date
2003-06Author
Felt, Andrew J.
Publisher
American Control Conference
Metadata
Show full item recordAbstract
We begin with a traditional model predictive control problem using the l1 norm in the objective function, and then allow the model parameters to be stochastic, with discrete distributions and finite support. We apply the nested decomposition algorithm for multistage stochastic linear programming to the resulting problem. The result is an algorithm for model predictive control that features the realism of model uncertainty, the potential speed of linear objective functions, and can be implemented in parallel.
Subject
Research Subject Categories::MATHEMATICS::Applied mathematics::Optimization, systems theory
Permanent Link
http://digital.library.wisc.edu/1793/79605Citation
Stochastic linear model predictive control using nested decomposition, Proceedings of the American Control Conference, Denver, CO, 2003, vol. 4, pp. 3602-3607.