*Self-optimizing Control (SOC) is to find appropriate controlled variables for which implementation of feedback control yields near-optimal operation regardless of variation in disturbances. With the properties of easy implementation and fast response, SOC has been widely adopted in the field of process industry. A big issue in the SOC is that the disturbances change the active constraints which are assumed to be invariant over the whole process. In this paper, we proposed a SOC method with considering such active set changes. Without elaborate and costly model calibration under different disturbances, we identify the nonlinear dynamical model equations only based on the historical operating data and then derive static model equations. This enables formulation of the SOC based control structure design as a constrained quadratic optimization problem and the implementation of parametric program to cover the changes in active set. Parametric program divides the disturbance space into regions with different sets of active constraints and find the piecewise linear solutions. The online implementation of optimal operation follows the solutions in different regions and the values of controlled variables can be used for regions detection. The proposed approach is validated with a simulation study of a Modelica-based chilled-water plant.*


Control Structure Design of Building Hvac Systems Using a Data-Driven Self-Optimizing Control With Active Set Change

Division / Sponsors: 
Dynamic Systems & Control (DSCD)

Paper Proceedings: https://asmedigitalcollection.asme.org/DSCC/DSCC2020/volume/84270

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