Hierarchical Decentralized Reference Governor using Dynamic Constraint Tightening for Constrained Cascade Systems
Shahram Aghaei, Abolghasem Daeichian, Vicen\c{c} Puig

TL;DR
This paper introduces a hierarchical decentralized reference governor with dynamic constraint tightening for cascade systems, ensuring constraint satisfaction and stability through receding horizon optimization and decentralized algorithms.
Contribution
It presents a novel hierarchical decentralized RG approach with dynamic constraint tightening, enhancing feasibility and reducing conservatism in large-scale cascade systems.
Findings
Guarantees constraint satisfaction in transient conditions
Ensures stability and convergence of the control scheme
Successfully applied to a cascade of three reactors
Abstract
This paper proposes a hierarchical decentralized reference governor for constrained cascade systems. The reference governor (RG) approach is reformulated in terms of receding horizon strategy such that a locally receding horizon optimization is obtained for each subsystem with a pre-established prediction horizon. The algorithm guarantees that not only the nominal overall closed-loop system without any constraint is recoverable but also the state and control constraints are satisfied in transient conditions. Also, considering unfeasible reference signals, the output of any subsystem goes locally to the nearest feasible value. The proposed dynamic constraint tightening strategy uses a receding horizon to reduce the conservatism of conventional robust RGs. Moreover, a decentralized implementation of the algorithms used to compute tightened constraints and output admissible sets is…
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