Chance Constraint based Design of Controllers for Linear Uncertain Systems


Nandi, S., and Singh, T.


2017 American Control Conference, May 24-May 26, Seattle, Washington.


This paper considers the problem of state-to-state transition with state and control constraints, for a linear system with model parameter uncertainties. Polynomial chaos is used to transform the stochastic model to a deterministic surrogate model. This surrogate model is used to pose a chance constrained optimal control problem where the state constraints and the residual energy cost are represented in terms of the mean and variance of the stochastic states. The resulting convex optimization is illustrated on the problem of rest-to-rest maneuver of the benchmark floating oscillator.