Economic performance assessment of process control: A probability optimization approach

In this paper, a probability optimization approach for economic performance assessment of the constrained process control under uncertainty is presented. Performance evaluation problems are formulated as the stochastic problems which incorporate the uncertainties in both process operation and economic objective. Such problem formulation helps to identify the opportunity of improving the profitability of the process by taking appropriate risks. Both the steady state economic benefit and the optimal operation conditions can be obtained by solving the defined economic optimization problems. Further, the proposed method uses the LQG benchmark other than conventional minimum variance control (MVC) benchmark to estimate potential of variance reduction, which results in a more reasonable performance assessment. The proposed algorithm is also illustrated by a simulated example of the model predictive control system.