Coordinated design and control optimization of nonlinear processes

Abstract On a small time-scale, disturbances to a process can lead to off-spec production, decreased profitability and the violation of hard process constraints, creating unsafe conditions. A strategy is presented for the design of processes that are operationally optimal, as well as steady-state optimal, and that operate prudently far from hard constraints. In addition to the evaluation of an economic objective, each potential design is evaluated for its controllability, using the closed-loop response to several disturbances, simulated with model predictive control (MPC) algorithms. These algorithms provide excellent responses to unmeasured disturbances, allow for the inclusion of constraints and are fairly insensitive to the tuning parameters, allowing for an evaluation of the inherent controllability of a process. This strategy has been applied to a fermentation process with complex chemical and physical interactions and characterized by hysteresis and periodic behavior for some ranges of its design parameters. A simple optimization of venture profit leads to a design that is highly constrained and unstable. Using the above strategy, it is demonstrated that alternative designs exist with improved controllability, but without retreating from the design constraints. This is counterintuitive and contrary to the results of several case studies. Furthermore, the design remains unstable.

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