Regression-based LP Solver for Chance-Constrained Finite Horizon Optimal Control with Nonconvex Constraints
This paper presents a novel algorithm for finite-horizon optimal control problems subject to additive Gaussian-distributed stochastic disturbance and chance constraints that are defined over feasible, non-convex state spaces. Our previous work [1] proposed a branch and bound-based algorithm that can...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers
2011
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| Online Access: | http://hdl.handle.net/1721.1/67723 https://orcid.org/0000-0002-1057-3940 https://orcid.org/0000-0002-8293-0492 |