Practical Computational Approach for the Stability Analysis of Fuzzy Model-Based Predictive Control of Substrate and Biomass in Activated Sludge Processes

This paper presents a procedure for the closed‑loop stability analysis of a certain variant of the strategy called Fuzzy Model‑Based Predictive Control (FMBPC), with a model of the Takagi‑Sugeno type, applied to the wastewater treatment process known as the Activated Sludge Process (ASP), with the a...

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Main Authors: Pedro M. Vallejo LLamas, Pastora Vega
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Processes
Subjects:
Online Access:https://www.mdpi.com/2227-9717/9/3/531
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spelling doaj-f4a71ac4dfdf4307b78046cddecba16e2021-03-18T00:01:26ZengMDPI AGProcesses2227-97172021-03-01953153110.3390/pr9030531Practical Computational Approach for the Stability Analysis of Fuzzy Model-Based Predictive Control of Substrate and Biomass in Activated Sludge ProcessesPedro M. Vallejo LLamas0Pastora Vega1Supervision and Process Control Research Group, Computing and Automatic Department, University of Salamanca, 37008 Salamanca, SpainSupervision and Process Control Research Group, Computing and Automatic Department, University of Salamanca, 37008 Salamanca, SpainThis paper presents a procedure for the closed‑loop stability analysis of a certain variant of the strategy called Fuzzy Model‑Based Predictive Control (FMBPC), with a model of the Takagi‑Sugeno type, applied to the wastewater treatment process known as the Activated Sludge Process (ASP), with the aim of simultaneously controlling the substrate concentration in the effluent (one of the main variables that should be limited according to environmental legislations) and the biomass concentration in the reactor. This case study was chosen both for its environmental relevance and for special process characteristics that are of great interest in the field of nonlinear control, such as strong nonlinearity, multivariable nature, and its complex dynamics, a consequence of its biological nature. The stability analysis, both of fuzzy systems (FS) and the very diverse existing strategies of nonlinear predictive control (NLMPC), is in general a mathematically laborious task and difficult to generalize, especially for processes with complex dynamics. To try to minimize these difficulties, in this article, the focus was placed on the mathematical simplification of the problem, both with regard to the mathematical model of the process and the stability analysis procedures. Regarding the mathematical model, a state-space model of discrete linear time-varying (DLTV), equivalent to the starting fuzzy model (previously identified), was chosen as the base model. Furthermore, in a later step, the DLTV model was approximated to a local model of type discrete linear time-invariant (DLTI). As regards the stability analysis itself, a computational method was developed that greatly simplified this difficult task (in a local environment of an operating point), compared to other existing methods in the literature. The use of the proposed method provides useful conclusions for the closed‑loop stability analysis of the considered FMBPC strategy, applied to an ASP process; at the same time, the possibility that the method may be useful in a more general way, for similar fuzzy and predictive strategies, and for other complex processes, was observed.https://www.mdpi.com/2227-9717/9/3/531stability analysisfuzzy model‑based predictive controlTakagi‑Sugenomultivariable controlwastewater treatment plantactivated sludge process
collection DOAJ
language English
format Article
sources DOAJ
author Pedro M. Vallejo LLamas
Pastora Vega
spellingShingle Pedro M. Vallejo LLamas
Pastora Vega
Practical Computational Approach for the Stability Analysis of Fuzzy Model-Based Predictive Control of Substrate and Biomass in Activated Sludge Processes
Processes
stability analysis
fuzzy model‑based predictive control
Takagi‑Sugeno
multivariable control
wastewater treatment plant
activated sludge process
author_facet Pedro M. Vallejo LLamas
Pastora Vega
author_sort Pedro M. Vallejo LLamas
title Practical Computational Approach for the Stability Analysis of Fuzzy Model-Based Predictive Control of Substrate and Biomass in Activated Sludge Processes
title_short Practical Computational Approach for the Stability Analysis of Fuzzy Model-Based Predictive Control of Substrate and Biomass in Activated Sludge Processes
title_full Practical Computational Approach for the Stability Analysis of Fuzzy Model-Based Predictive Control of Substrate and Biomass in Activated Sludge Processes
title_fullStr Practical Computational Approach for the Stability Analysis of Fuzzy Model-Based Predictive Control of Substrate and Biomass in Activated Sludge Processes
title_full_unstemmed Practical Computational Approach for the Stability Analysis of Fuzzy Model-Based Predictive Control of Substrate and Biomass in Activated Sludge Processes
title_sort practical computational approach for the stability analysis of fuzzy model-based predictive control of substrate and biomass in activated sludge processes
publisher MDPI AG
series Processes
issn 2227-9717
publishDate 2021-03-01
description This paper presents a procedure for the closed‑loop stability analysis of a certain variant of the strategy called Fuzzy Model‑Based Predictive Control (FMBPC), with a model of the Takagi‑Sugeno type, applied to the wastewater treatment process known as the Activated Sludge Process (ASP), with the aim of simultaneously controlling the substrate concentration in the effluent (one of the main variables that should be limited according to environmental legislations) and the biomass concentration in the reactor. This case study was chosen both for its environmental relevance and for special process characteristics that are of great interest in the field of nonlinear control, such as strong nonlinearity, multivariable nature, and its complex dynamics, a consequence of its biological nature. The stability analysis, both of fuzzy systems (FS) and the very diverse existing strategies of nonlinear predictive control (NLMPC), is in general a mathematically laborious task and difficult to generalize, especially for processes with complex dynamics. To try to minimize these difficulties, in this article, the focus was placed on the mathematical simplification of the problem, both with regard to the mathematical model of the process and the stability analysis procedures. Regarding the mathematical model, a state-space model of discrete linear time-varying (DLTV), equivalent to the starting fuzzy model (previously identified), was chosen as the base model. Furthermore, in a later step, the DLTV model was approximated to a local model of type discrete linear time-invariant (DLTI). As regards the stability analysis itself, a computational method was developed that greatly simplified this difficult task (in a local environment of an operating point), compared to other existing methods in the literature. The use of the proposed method provides useful conclusions for the closed‑loop stability analysis of the considered FMBPC strategy, applied to an ASP process; at the same time, the possibility that the method may be useful in a more general way, for similar fuzzy and predictive strategies, and for other complex processes, was observed.
topic stability analysis
fuzzy model‑based predictive control
Takagi‑Sugeno
multivariable control
wastewater treatment plant
activated sludge process
url https://www.mdpi.com/2227-9717/9/3/531
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