We propose a robust control strategy, model predictive control under chance constraints, to deal with multivariable constrained control problems. Both model and disturbance uncertainties are considered and assumed to be correlated multivariate stochastic variables. The output constraints are to be held with a predefined probability in respect of the entire horizon. The problem formulated is a stochastic program under joint probabilistic constraints. Using an efficient sampling method this problem is relaxed to a nonlinear programming problem which can be solved by SQP. Simulation results of a distillation column control show the performances of the proposed strategy.