Stochastic Model Predictive Control Using Simplified Affine Disturbance Feedback for Chance-Constrained Systems

This letter covers the model predictive control of linear discrete-time systems subject to stochastic additive disturbances and chance constraints on their state input. We propose a simplified parameterization under framework affine disturbance feedback, we show that our method is equivalent over family feedback policies. Using method, associated finite-horizon optimization can be computed efficiently, with slight increase in conservativeness compared conventional parameterization.