This paper presents a new methodology to integrate process design and control. The key idea in this method is to represent the system's closed-loop nonlinear behaviour as a linear state space model complemented with uncertain model parameters. Then, robust control tools are applied to calculate bounds on the process stability, the process feasibility and the worst-case scenario. The new methodology was applied to the simultaneous design and control of a mixing tank process. The resulting design avoids the solution of computationally intensive dynamic optimizations since the integration of design and control problem is reduced to a nonlinear constrained optimization problem. (c) 2007 Elsevier Ltd. All rights reserved.