A YALMIP-implemented numerical framework computes chance-constraint probabilities and gradients via characteristic-function inversion for non-Gaussian disturbances in stochastic MPC.
and Buehler, Edward A
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A characteristic function framework for chance constraint programming in stochastic model predictive control
A YALMIP-implemented numerical framework computes chance-constraint probabilities and gradients via characteristic-function inversion for non-Gaussian disturbances in stochastic MPC.