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Stochastic model predictive control with joint chance constraints
2017
International Journal of Control
This article considers the stochastic optimal control of discrete-time linear systems subject to (possibly) unbounded stochastic disturbances, hard constraints on the manipulated variables, and joint chance constraints on the states. A tractable convex second-order cone program (SOCP) is derived for calculating the receding-horizon control law at each time step. Feedback is incorporated during prediction by parametrizing the control law as an affine function of the disturbances. Hard input
doi:10.1080/00207179.2017.1323351
fatcat:6twj4dibffaqxcrjnrbtnzz7gu