Chance‐constrained model predictive control a reformulated approach suitable for sewer networks

Autor: Hans Henrik Niemann, Jan Lorenz Svensen, Niels Kjølstad Poulsen, Anne Katrine Vinther Falk
Rok vydání: 2021
Předmět:
Zdroj: Svensen, J L, Niemann, H H, Falk, A K V & Poulsen, N K 2021, ' Chance-constrained model predictive control : a reformulated approach suitable for sewer networks ', Advanced Control for Applications: Engineering and Industrial Systems, vol. 3, no. 4, e94 . https://doi.org/10.1002/adc2.94
ISSN: 2578-0727
DOI: 10.1002/adc2.94
Popis: In this work, a revised formulation of Chance-Constrained (CC) Model Predictive Control (MPC) is presented. The focus of this work is on the mathematical formulation of the revised CC-MPC, and the reason behind the need for its revision. The revised formulation is given in the context of sewer systems, and their weir overflow structures. A linear sewer model of the Astlingen Benchmark sewer model is utilized to illustrate the application of the formulation, both mathematically and performance-wise through simulations. Based on the simulations, a comparison of performance is done between the revised CC-MPC and a comparable deterministic MPC, with a focus on overflow avoidance, computation time, and operational behavior. The simulations show similar performance for overflow avoidance for both types of MPC, while the computation time increases slightly for the CC-MPC, together with operational behaviors getting limited
14 pages, 13 figures, 2 tables, submitted to journal of Advanced Control and Application, july 2020
Databáze: OpenAIRE
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