Fault-Tolerant Model Predictive Control Applied to a Sewer Network
Source abstract
Abstract
This paper presents a Fault-Tolerant Model Predictive Control (FTMPC) algorithm applied to a simulation model for sewer networks. The aim of this work is to preserve the operation of the predictive controller as much as possible, in accordance with its operational objectives, when there may be anomalies affecting the elements of the control system, mainly sensors and actuators. For this purpose, a fault detection and diagnosis system (FDD) based on a moving window principal component analysis technique (MWPCA) will be developed to provide an online fault monitoring solution for large-scale complex processes (e.g., sewer systems) with dynamically changing characteristics, and a reconfiguration algorithm for the MPC controller taking advantage of its own features such as constraint handling. Comparing the results obtained considering various types of faults, with situations of normal controlled operation and with the behavior of the sewer network when no control is applied, will allow some conclusions to be drawn at the end.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Fault Detection and Control Systems · Water Systems and Optimization · Advanced Control Systems Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Computing and Automation Department, Higher Technical School of Industrial Engineering, University of Salamanca, 37700 Béjar, Spain
System Engineering and Automatic Control Department, School of Industrial Engineering (EII), University of Valladolid, 47011 Valladolid, Spain
Computing and Automation Department, Faculty of Science, University of Salamanca, 37008 Salamanca, Spain
Funding
Spanish Government
References (40)
Show source-provided references
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