Two-layered dynamic control for simultaneous set-point tracking and improved economic performance. (January 2021) - Ravi, Arvind; Kaisare, Niket S.
Abstract: This work introduces a multi-objective optimization strategy to handle conflicting set-point tracking and economic objectives in a two-layer hierarchical control framework. A dynamic multi-objective real-time optimizer (DMO), incorporated in the upper layer, handles multiple control objectives with set-point tracking being the higher priority objective and computes optimal plant trajectories. This plant-wide trajectory information is communicated to the lower-layer model predictive control (MPC) operating at a faster sampling rate. The conventional weight-based and lexicographical method for the DMO are discussed. A new algorithm is conceptualized based on the lexicographical method to handle prioritized objectives. The proposed algorithm modifies the higher priority tracking objective and establishes improved economic performance compared to the conventional techniques, with minimal effect on the conflicting tracking objective, through a systematic choice of the preferred Pareto solution. The proposed algorithm's efficacy, within the hierarchical framework, is analyzed using two case studies: A polymerization reactor and a multi-unit reactor–separator system. Highlights: Dynamic multi-objective control solved using two-layer hierarchical architecture. Upper layer handles priority-based multi-objectives using lexicographic approach. Pareto-based trade-off of tracking cost proposed to improve economic performance. Optimal trajectory implemented by lower layer MPC. Two case studies demonstrate flexibility and performance of proposed approach.