In this paper, a semianalytical parametric approximation of chance constraints, called the split-Bernstein approximation, is employed to construct a framework for posing and solving chance-constrained optimal control problems. Dynamic systems with deterministic as well as stochastically perturbed dynamics are considered. In both cases, the chance-constrained optimal control problem is converted into a chance-constrained program, which is transcribed to a nonlinear program using the split-Bernstein approximation. Discretization of deterministic optimal control problems is performed via pseudospectral collocation. For systems perturbed by white noise, a shooting method is used that imposes dynamic constraints implicitly via ensemble propagation. The split-Bernstein approximation of chance constraints allows the solution of the resulting nonlinear program using off-the-shelf gradient-based nonlinear program solvers.


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    Title :

    Split-Bernstein Approach to Chance-Constrained Optimal Control


    Contributors:
    Zhao, Zinan (author) / Kumar, Mrinal (author)

    Published in:

    Publication date :

    2017-08-11


    Size :

    14 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






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