A new methodology for simultaneous design and control under process disturbances and parameter uncertainty is presented using power series expansions (PSE) approximations. The key idea in this methodology is to back-off from the optimal steady-state design, which might be infeasible because of process dynamics and parameter uncertainty, to obtain the optimal design parameters that result in a dynamically feasible and economically attractive process. The work focuses on calculating various optimal design and control parameters by solving a set of optimization problems in an iterative manner using mathematical expressions obtained from PSE. These approximations are used to determine the direction in the search of optimal design parameters and operating conditions that is required for an economically attractive and dynamically feasible process. The proposed method was tested on a nonisothermal CSTR, and the results were compared with the formal integration process. The effect of the methodologys key tuning parameters is also presented. The results show that this method has the potential to address the integration of design and control of dynamic systems under uncertainty at low computational costs.