Abstract
Economic optimal operation typically involves operating as close as possible to the active constraints. However, in the presence of disturbances it is necessary to back-off from the constraints in order to avoid violating them. The backoff approach aims at selecting the control structure that minimizes the economic loss associated with the required constraint backoffs. This paper revisits the backoff approach and proposes a framework for estimating the constraint backoffs based on well-known elements of internal model control (IMC) theory, such as an automatic procedure for tuning the IMC low-pass filters, a stability condition, and an uncertainty representation based on diagonal input multiplicative uncertainty. Since the constraint backoffs are estimated using a linear dynamic model, the inclusion of input multiplicative uncertainty allows introducing conservatism in the estimation of the backoffs, which is required in order to avoid constraint violations. A forced-circulation evaporator benchmark problem is used to illustrate the approach.
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