Gabriela Cembrano - Academia.edu (original) (raw)

Papers by Gabriela Cembrano

Zenodo (CERN European Organization for Nuclear Research), Sep 3, 2020

The worldwide growing demand of water supply requires a proper management of the available hydrau... more The worldwide growing demand of water supply requires a proper management of the available hydraulic resources. One of the major concerns in the operation of water distribution networks (WDNs) is the existence of leakages, due to the high operational costs for the water utilities. Leaks can produce substantial economic losses, infrastructure damage and even health risks. Therefore, leak detection and isolation methodologies are widely researched. One the one hand, model-based approaches exploit the existence of a hydraulic model of the considered WDN, as well as the availability of hydraulic measurements like inlet flow and pressure, and sensorized inner nodes pressure, to tackle the leak localization task. The suitability of these methods has been confirmed by numerous works during the years. On the other hand, the sources of information in the majority of water networks are rather limited, and other interesting measurements are not available, like water demands at the junctions, flows between inner nodes, etc. Thus, datadriven approaches, which have a reduced or non-existent dependency on a hydraulic model, can be helpful to locate leaks in WDNs that lack the mentioned measurements and modelling. This abstract presents the combined utilization of a model-based and a novel data-driven methodology to locate leaks in the concrete case of the challenge proposed at BattLeDIM 2020. The division of the introduced network (L-Town) in three areas allows to determine the usage of one of the approaches at each one of these areas, depending on their concrete characteristics. Besides, both methods allow to solve the multi-leak problem in a proper way, which entails a further step with regard to the classical single-leak assumption.

HIC 2018. 13th International Conference on Hydroinformatics, Sep 20, 2018

This paper presents a FTC framework for a Real-Time MPC-based Controller applied to Integrated Ur... more This paper presents a FTC framework for a Real-Time MPC-based Controller applied to Integrated Urban Drainage and Sanitation Systems (UDSSs) which was proposed in the LIFE EFFIDRAIN project. This project deals with the pollution of surface waters due to CSOs and overflows from UDSSs during wet weather. The main purpose of the proposed FTC framework is to preserve as much as possible, the performance of the MPC-based Controller in terms of operation objectives when anomalies affecting the integrated ICT elements (sensors and actuators) occurs. The performance of the FTC controller has been tested using a realistic case of study.

Water, Dec 21, 2019

Leaks in water distribution networks (WDNs) are one of the main reasons for water loss during flu... more Leaks in water distribution networks (WDNs) are one of the main reasons for water loss during fluid transportation. Considering the worldwide problem of water scarcity, added to the challenges that a growing population brings, minimizing water losses through leak detection and localization, timely and efficiently using advanced techniques is an urgent humanitarian need. There are numerous methods being used to localize water leaks in WDNs through constructing hydraulic models or analyzing flow/pressure deviations between the observed data and the estimated values. However, from the application perspective, it is very practical to implement an approach which does not rely too much on measurements and complex models with reasonable computation demand. Under this context, this paper presents a novel method for leak localization which uses a data-driven approach based on limit pressure measurements in WDNs with two stages included: (1) Two different machine learning classifiers based on linear discriminant analysis (LDA) and neural networks (NNET) are developed to determine the probabilities of each node having a leak inside a WDN; (2) Bayesian temporal reasoning is applied afterwards to rescale the probabilities of each possible leak location at each time step after a leak is detected, with the aim of improving the localization accuracy. As an initial illustration, the hypothetical benchmark Hanoi district metered area (DMA) is used as the case study to test the performance of the proposed approach. Using the fitting accuracy and average topological distance (ATD) as performance indicators, the preliminary results reaches more than 80% accuracy in the best cases.

Journal of Water Resources Planning and Management, May 1, 2022

The worldwide growing demand of water supply requires a proper management of the available hydrau... more The worldwide growing demand of water supply requires a proper management of the available hydraulic resources. One of the major concerns in the operation of water distribution networks (WDNs) is the existence of leakages, due to the high operational costs for the water utilities. Leaks can produce substantial economic losses, infrastructure damage and even health risks. Therefore, leak detection and isolation methodologies are widely researched. One the one hand, model-based approaches exploit the existence of a hydraulic model of the considered WDN, as well as the availability of hydraulic measurements like inlet flow and pressure, and sensorized inner nodes pressure, to tackle the leak localization task. The suitability of these methods has been confirmed by numerous works during the years. On the other hand, the sources of information in the majority of water networks are rather limited, and other interesting measurements are not available, like water demands at the junctions, flows between inner nodes, etc. Thus, datadriven approaches, which have a reduced or non-existent dependency on a hydraulic model, can be helpful to locate leaks in WDNs that lack the mentioned measurements and modelling. This abstract presents the combined utilization of a model-based and a novel data-driven methodology to locate leaks in the concrete case of the challenge proposed at BattLeDIM 2020. The division of the introduced network (L-Town) in three areas allows to determine the usage of one of the approaches at each one of these areas, depending on their concrete characteristics. Besides, both methods allow to solve the multi-leak problem in a proper way, which entails a further step with regard to the classical single-leak assumption.

Energies, Aug 5, 2019

This paper proposes a health-aware control approach for drinking water transport networks. This a... more This paper proposes a health-aware control approach for drinking water transport networks. This approach is based on an economic model predictive control (MPC) that considers an additional goal with the aim of extending the components and system reliability. The components and system reliability are incorporated into the MPC model using a Linear Parameter Varying (LPV) modeling approach. The MPC controller uses additionally an economic objective function that determines the optimal filling/emptying sequence of the tanks considering that electricity price varies between day and night and that the demand also follows a 24-h repetitive pattern. The proposed LPV-MPC control approach allows considering the model nonlinearities by embedding them in the parameters. The values of these varying parameters are updated at each iteration taking into account the new values of the scheduling variables. In this way, the optimization problem associated with the MPC problem is solved by means of Quadratic Programming (QP) to avoid the use of nonlinear programming. This iterative approach reduces the computational load compared to the solution of a nonlinear optimization problem. A case study based on the Barcelona water transport network is used for assessing the proposed approach performance.

Journal of Process Control, Feb 1, 2023

IFAC-PapersOnLine, Jul 1, 2017

A distributed set-membership approach is proposed for the state estimation of largescale systems.... more A distributed set-membership approach is proposed for the state estimation of largescale systems. The uncertain system states are bounded in a sequence of the distributed setmembership estimators considering unknown-but-bounded system disturbances and measurement noise. In the framework of the set-membership approach, the measurement consistency test is implemented by finding parameterized intersection zonotopes. The size of the intersection zonotope is minimized by solving an optimization problem including a sequence of linear/bilinear matrix inequalities based on the weighted 2-norm criterion of the generator matrix. Meanwhile, for the distributed set-membership estimators, the partial projection method is considered to correct the estimation of the neighbor state. On the other hand, an on-line method is also provided. Finally, the proposed distributed set-membership approach is verified in a case study based on a urban drainage network.

IFAC-PapersOnLine, Jul 1, 2017

This paper considers actuator-fault estimation for discrete-time descriptor systems with unknown ... more This paper considers actuator-fault estimation for discrete-time descriptor systems with unknown but bounded system disturbance and measurement noise. A zonotopic fault estimation filter is designed based on the analysis of fault detectability indexes. To ensure estimation accuracy, the filter gain in the zonotopic fault estimation filter is optimized through the zonotope minimization. The designed zonotopic filter not only can estimate fault magnitudes, but it also provides fault estimation results in an interval, i.e. the upper and lower bounds of fault magnitudes. Moreover, the proposed fault estimation filter has a non-singular structure and hence is easy to implement. Finally, simulation results are provided to illustrate the effectiveness of the proposed method.

Engineering Applications of Artificial Intelligence, Mar 1, 2016

This paper presents a control scheme which uses a combination of linear Model Predictive Control ... more This paper presents a control scheme which uses a combination of linear Model Predictive Control (MPC) and a Constraint Satisfaction Problem (CSP) to solve the non-linear operational optimal control of Drinking Water Networks (DWNs). The methodology has been divided into two functional layers: First, a CSP algorithm is used to transfer non-linear DWNs pressure equations into linear constraints on flows and tank volumes, which can enclose the feasible solution set of the hydraulic non-linear problem during the optimization process. Then, a linear MPC with tightened constraints produced in the CSP layer is solved to generate control strategies which optimize the control objectives. The proposed approach is simulated using Epanet to represent the real DWNs. Non-linear MPC is used for validation. To illustrate the performance of the proposed approach, a case study based on the Richmond water network is used and a realistic example, D-Town benchmark network, is added as a supplementary case study.

Water Science and Technology, May 15, 2020

Pollution caused by combined sewer overflows has become a global threat to the environment. Under... more Pollution caused by combined sewer overflows has become a global threat to the environment. Under this challenge, quality-based real-time control (RTC) is considered as an effective approach to minimize pollution through generating optimal operation strategies for the sewer infrastructure. To suit the fast computation requirement of RTC implementation, simplified quality models are required. However, due to the hydrological complexity, it is not easy to develop simplified quality models which are amenable to be used in real-time computations. Under this context, this paper contributes a preliminary analysis of influencing factors for the quality models of sewer networks in order to give supportive knowledge for both model development and application. Conceptual quality models which were proposed previously by the authors, with total suspended solids (TSS) as quality indicator, are used in this study. A clustering algorithm is used for exploratory analysis. Further analysis about the correlations between different factors and model performance is also carried out. The study and analysis are demonstrated on a real pilot based on the Louis Fargue urban catchment in Bordeaux. Conclusive results about the influencing factors, flow rate, rain intensity and pipe length, as well as their correlations with the TSS models are elaborated. Key words | analysis, influencing factor, quality model, real-time control, total suspended solid HIGHLIGHTS • Influencing factors have been analyzed for the performance of TSS simplified models. • Flow rate, sewer length and rain intensity are the three influencing factors. • Correlations between factors and model performance are elaborated. • Pollution-based real-time control can be applied using these simplified quality models. • More effective integrated management can be contributed through this study.

Integrated control of urban drainage systems considering urban drainage networks (UDN), wastewate... more Integrated control of urban drainage systems considering urban drainage networks (UDN), wastewater treatment plants (WWTP) and the receiving environment seeks to minimize the impact of combined sewer overflow (CSO) to the receiving environment during wet weather. This paper will show first results of the integrated control of UDN and WWTP, obtained by LIFE-EFFIDRAIN, which is a collaborative project between academia and industry in Barcelona (Spain) and Bordeaux (France). Model predictive control (MPC) is applied for strategy optimization using conceptual hydraulic and quality variables, where the total suspended solid (TSS) concentration is selected as a representive of water quality. SWMM5 integrated with a lumped conceptual model of TSS (SWMM-TSS) is applied as virtual reality. The Perinot sewer network from Bordeaux is used as a case study for functional demonstration.

Computers & Chemical Engineering, Jun 1, 2021

Abstract Large-scale control systems tend to present a large number of alternative and back-up el... more Abstract Large-scale control systems tend to present a large number of alternative and back-up elements that, although not used in nominal operation, could be brought into play if necessary. Such hardware redundancy extends the fault tolerant capabilities of the system, while posing the problem of selecting the most suitable new system configuration. Accordingly, this paper aims to formulate the problem of, after a fault occurrence, selecting the (in some sense) optimal system configuration that maintains an admissible system performance until the restoration of the nominal service. The configuration selection is posed as a multi-objective mixed-integer program (MIP) solved using a lexicographic approach. Aiming at reducing the worst-case execution time, the analysis of necessary properties for the existence of an admissible solution, as well as how to manage the information obtained by evaluating such properties to be included in the MIP, are investigated. A portion of a water distribution network is used in order to validate the proposed solution.

IEEE Transactions on Control Systems and Technology, 2023

Model predictive control (MPC) can be used to manage combined urban drainage systems more efficie... more Model predictive control (MPC) can be used to manage combined urban drainage systems more efficiently for protection of human health and the environment, but examples of operational implementations are rare. This paper reviews more than 30 years of partly heterogeneous research on the topic. We propose a terminology for MPC of urban drainage systems and a hierarchical categorization where we emphasize four overall components: the "receding horizon principle", the "optimization model", the "optimization solver", and the "internal MPC model". Most of the reported optimization models share the trait of a multiobjective optimization based on a conceptual internal MPC model. However, there is a large variety of both convex and non-linear optimization models and optimization solvers as well as constructions of the internal MPC model. Furthermore, literature disagrees about the optimal length of the components in the receding horizon principle. The large number of MPC formulations and evaluation approaches makes it problematic to compare different MPC methods. This review highlights methods, challenges, and research gaps in order to make MPC of urban drainage systems accessible for researchers and practitioners from different disciplines. This will pave the way for shared understanding and further development within the field, and eventually lead to more operational implementations.

Annual Reviews in Control, 2023

IFAC-PapersOnLine, 2018

One of the relevant information provided by the prognostics and health management algorithms is t... more One of the relevant information provided by the prognostics and health management algorithms is the estimation of the Remaining Useful Life (RUL). The prediction of the expected RUL is very useful to decrease maintenance cost, operational downtime and safety hazards. This paper proposes a new strategy of health-aware Model Predictive Control (MPC) for a Linear Parameter Varying (LPV) system that includes as an additional goal extending the system RUL via their estimation using reliability tools. In this approach, the RUL maximization is included in the objective function of the LPV-MPC controller. The RUL is included in the MPC model as an extra parameter varying equation that considers the control action as scheduling variable. The proposed control approach allows the controller to accommodate to the parameter changes. Through computing an estimation of the state variables during prediction, the MPC model can be modified to the estimated state evolution at each time instant. Moreover, for solving the optimization problem by using a series of Quadratic Programs (QP) in each time instant, a new iterative approach is exhibited, which improves the computational efficiency. A pasteurization plant control system is used as a case study to illustrate the performance of the proposed approach.

Procedia Engineering, 2015

This paper describes an integrated model-based monitoring framework for leakage localization in d... more This paper describes an integrated model-based monitoring framework for leakage localization in district-metered areas (DMA) of water distribution networks, which takes advantage of the availability of a hydraulic model of the network. The leakage localization methodology is based on the use of flow and pressure sensors at the DMA inlets and a limited number of pressure sensors deployed inside the DMA. The placement of these sensors has been computed using an optimal sensor placement method based on a Genetic Algorithm optimization, which integrates the direct modelling approach (simulation) used to identify the location of leaks. The application of the resulting monitoring framework in a certain DMA of the Barcelona distribution network is provided and discussed using simulated leakage scenarios. The obtained results show that leakage detection and localization may be performed efficiently, reducing the required time for detection/localization, by following a simple procedure.

Journal of Water Resources Planning and Management, 2023

This article presents a novel response methodology for the operational recovery of a drinking wat... more This article presents a novel response methodology for the operational recovery of a drinking water network after an incident causes an interruption of service. The proposed optimization-based methodology allows computing the optimal set of interventions to be performed in order to mitigate, or even prevent, the impact of the incident on the network operation. Besides, a proof-of-concept scheme has been designed for the automatic generation of failure scenarios and the systematic implementation and validation of the proposed response methodology. Several results are presented to demonstrate the capability of the methodology to mitigate harmful incidents, as well as the performance improvements derived from the application of the obtained interventions.

Proceedings of the 39th IAHR World Congress, 2022

IFAC-PapersOnLine, 2015

In order to take into account the scarcity of the water resource and the increasing of the popula... more In order to take into account the scarcity of the water resource and the increasing of the population, the management of drinking water networks has to be improved with the use of new tools and actions that allows fighting against wasting water. The monitoring of drinking water networks is based on the use of sensors to locate malfunctions (leaks, quality/contamination events, etc.). Practical implementation has to be carried out by optimizing the placement of the number of sensors and improving the detection and localization of malfunctions. Techniques for the detection and localization of leaks have been proposed in the last years based on the evaluation of residuals obtained by means of the comparison between the measurements obtained by the sensors and the values obtained by simulating the water network in a leak free scenario. In this paper, a data-driven approach based on the use of statistical classifiers working in the residual space is proposed for leak localization. The classifiers are trained using leak data scenarios in all the nodes of the network considering uncertainty in demand distribution, additive noise in sensors and leak magnitude. Finally, the proposed approach is tested using the well-known Hanoi network benchmark.

Zenodo (CERN European Organization for Nuclear Research), Sep 3, 2020

The worldwide growing demand of water supply requires a proper management of the available hydrau... more The worldwide growing demand of water supply requires a proper management of the available hydraulic resources. One of the major concerns in the operation of water distribution networks (WDNs) is the existence of leakages, due to the high operational costs for the water utilities. Leaks can produce substantial economic losses, infrastructure damage and even health risks. Therefore, leak detection and isolation methodologies are widely researched. One the one hand, model-based approaches exploit the existence of a hydraulic model of the considered WDN, as well as the availability of hydraulic measurements like inlet flow and pressure, and sensorized inner nodes pressure, to tackle the leak localization task. The suitability of these methods has been confirmed by numerous works during the years. On the other hand, the sources of information in the majority of water networks are rather limited, and other interesting measurements are not available, like water demands at the junctions, flows between inner nodes, etc. Thus, datadriven approaches, which have a reduced or non-existent dependency on a hydraulic model, can be helpful to locate leaks in WDNs that lack the mentioned measurements and modelling. This abstract presents the combined utilization of a model-based and a novel data-driven methodology to locate leaks in the concrete case of the challenge proposed at BattLeDIM 2020. The division of the introduced network (L-Town) in three areas allows to determine the usage of one of the approaches at each one of these areas, depending on their concrete characteristics. Besides, both methods allow to solve the multi-leak problem in a proper way, which entails a further step with regard to the classical single-leak assumption.

HIC 2018. 13th International Conference on Hydroinformatics, Sep 20, 2018

This paper presents a FTC framework for a Real-Time MPC-based Controller applied to Integrated Ur... more This paper presents a FTC framework for a Real-Time MPC-based Controller applied to Integrated Urban Drainage and Sanitation Systems (UDSSs) which was proposed in the LIFE EFFIDRAIN project. This project deals with the pollution of surface waters due to CSOs and overflows from UDSSs during wet weather. The main purpose of the proposed FTC framework is to preserve as much as possible, the performance of the MPC-based Controller in terms of operation objectives when anomalies affecting the integrated ICT elements (sensors and actuators) occurs. The performance of the FTC controller has been tested using a realistic case of study.

Water, Dec 21, 2019

Leaks in water distribution networks (WDNs) are one of the main reasons for water loss during flu... more Leaks in water distribution networks (WDNs) are one of the main reasons for water loss during fluid transportation. Considering the worldwide problem of water scarcity, added to the challenges that a growing population brings, minimizing water losses through leak detection and localization, timely and efficiently using advanced techniques is an urgent humanitarian need. There are numerous methods being used to localize water leaks in WDNs through constructing hydraulic models or analyzing flow/pressure deviations between the observed data and the estimated values. However, from the application perspective, it is very practical to implement an approach which does not rely too much on measurements and complex models with reasonable computation demand. Under this context, this paper presents a novel method for leak localization which uses a data-driven approach based on limit pressure measurements in WDNs with two stages included: (1) Two different machine learning classifiers based on linear discriminant analysis (LDA) and neural networks (NNET) are developed to determine the probabilities of each node having a leak inside a WDN; (2) Bayesian temporal reasoning is applied afterwards to rescale the probabilities of each possible leak location at each time step after a leak is detected, with the aim of improving the localization accuracy. As an initial illustration, the hypothetical benchmark Hanoi district metered area (DMA) is used as the case study to test the performance of the proposed approach. Using the fitting accuracy and average topological distance (ATD) as performance indicators, the preliminary results reaches more than 80% accuracy in the best cases.

Journal of Water Resources Planning and Management, May 1, 2022

The worldwide growing demand of water supply requires a proper management of the available hydrau... more The worldwide growing demand of water supply requires a proper management of the available hydraulic resources. One of the major concerns in the operation of water distribution networks (WDNs) is the existence of leakages, due to the high operational costs for the water utilities. Leaks can produce substantial economic losses, infrastructure damage and even health risks. Therefore, leak detection and isolation methodologies are widely researched. One the one hand, model-based approaches exploit the existence of a hydraulic model of the considered WDN, as well as the availability of hydraulic measurements like inlet flow and pressure, and sensorized inner nodes pressure, to tackle the leak localization task. The suitability of these methods has been confirmed by numerous works during the years. On the other hand, the sources of information in the majority of water networks are rather limited, and other interesting measurements are not available, like water demands at the junctions, flows between inner nodes, etc. Thus, datadriven approaches, which have a reduced or non-existent dependency on a hydraulic model, can be helpful to locate leaks in WDNs that lack the mentioned measurements and modelling. This abstract presents the combined utilization of a model-based and a novel data-driven methodology to locate leaks in the concrete case of the challenge proposed at BattLeDIM 2020. The division of the introduced network (L-Town) in three areas allows to determine the usage of one of the approaches at each one of these areas, depending on their concrete characteristics. Besides, both methods allow to solve the multi-leak problem in a proper way, which entails a further step with regard to the classical single-leak assumption.

Energies, Aug 5, 2019

This paper proposes a health-aware control approach for drinking water transport networks. This a... more This paper proposes a health-aware control approach for drinking water transport networks. This approach is based on an economic model predictive control (MPC) that considers an additional goal with the aim of extending the components and system reliability. The components and system reliability are incorporated into the MPC model using a Linear Parameter Varying (LPV) modeling approach. The MPC controller uses additionally an economic objective function that determines the optimal filling/emptying sequence of the tanks considering that electricity price varies between day and night and that the demand also follows a 24-h repetitive pattern. The proposed LPV-MPC control approach allows considering the model nonlinearities by embedding them in the parameters. The values of these varying parameters are updated at each iteration taking into account the new values of the scheduling variables. In this way, the optimization problem associated with the MPC problem is solved by means of Quadratic Programming (QP) to avoid the use of nonlinear programming. This iterative approach reduces the computational load compared to the solution of a nonlinear optimization problem. A case study based on the Barcelona water transport network is used for assessing the proposed approach performance.

Journal of Process Control, Feb 1, 2023

IFAC-PapersOnLine, Jul 1, 2017

A distributed set-membership approach is proposed for the state estimation of largescale systems.... more A distributed set-membership approach is proposed for the state estimation of largescale systems. The uncertain system states are bounded in a sequence of the distributed setmembership estimators considering unknown-but-bounded system disturbances and measurement noise. In the framework of the set-membership approach, the measurement consistency test is implemented by finding parameterized intersection zonotopes. The size of the intersection zonotope is minimized by solving an optimization problem including a sequence of linear/bilinear matrix inequalities based on the weighted 2-norm criterion of the generator matrix. Meanwhile, for the distributed set-membership estimators, the partial projection method is considered to correct the estimation of the neighbor state. On the other hand, an on-line method is also provided. Finally, the proposed distributed set-membership approach is verified in a case study based on a urban drainage network.

IFAC-PapersOnLine, Jul 1, 2017

This paper considers actuator-fault estimation for discrete-time descriptor systems with unknown ... more This paper considers actuator-fault estimation for discrete-time descriptor systems with unknown but bounded system disturbance and measurement noise. A zonotopic fault estimation filter is designed based on the analysis of fault detectability indexes. To ensure estimation accuracy, the filter gain in the zonotopic fault estimation filter is optimized through the zonotope minimization. The designed zonotopic filter not only can estimate fault magnitudes, but it also provides fault estimation results in an interval, i.e. the upper and lower bounds of fault magnitudes. Moreover, the proposed fault estimation filter has a non-singular structure and hence is easy to implement. Finally, simulation results are provided to illustrate the effectiveness of the proposed method.

Engineering Applications of Artificial Intelligence, Mar 1, 2016

This paper presents a control scheme which uses a combination of linear Model Predictive Control ... more This paper presents a control scheme which uses a combination of linear Model Predictive Control (MPC) and a Constraint Satisfaction Problem (CSP) to solve the non-linear operational optimal control of Drinking Water Networks (DWNs). The methodology has been divided into two functional layers: First, a CSP algorithm is used to transfer non-linear DWNs pressure equations into linear constraints on flows and tank volumes, which can enclose the feasible solution set of the hydraulic non-linear problem during the optimization process. Then, a linear MPC with tightened constraints produced in the CSP layer is solved to generate control strategies which optimize the control objectives. The proposed approach is simulated using Epanet to represent the real DWNs. Non-linear MPC is used for validation. To illustrate the performance of the proposed approach, a case study based on the Richmond water network is used and a realistic example, D-Town benchmark network, is added as a supplementary case study.

Water Science and Technology, May 15, 2020

Pollution caused by combined sewer overflows has become a global threat to the environment. Under... more Pollution caused by combined sewer overflows has become a global threat to the environment. Under this challenge, quality-based real-time control (RTC) is considered as an effective approach to minimize pollution through generating optimal operation strategies for the sewer infrastructure. To suit the fast computation requirement of RTC implementation, simplified quality models are required. However, due to the hydrological complexity, it is not easy to develop simplified quality models which are amenable to be used in real-time computations. Under this context, this paper contributes a preliminary analysis of influencing factors for the quality models of sewer networks in order to give supportive knowledge for both model development and application. Conceptual quality models which were proposed previously by the authors, with total suspended solids (TSS) as quality indicator, are used in this study. A clustering algorithm is used for exploratory analysis. Further analysis about the correlations between different factors and model performance is also carried out. The study and analysis are demonstrated on a real pilot based on the Louis Fargue urban catchment in Bordeaux. Conclusive results about the influencing factors, flow rate, rain intensity and pipe length, as well as their correlations with the TSS models are elaborated. Key words | analysis, influencing factor, quality model, real-time control, total suspended solid HIGHLIGHTS • Influencing factors have been analyzed for the performance of TSS simplified models. • Flow rate, sewer length and rain intensity are the three influencing factors. • Correlations between factors and model performance are elaborated. • Pollution-based real-time control can be applied using these simplified quality models. • More effective integrated management can be contributed through this study.

Integrated control of urban drainage systems considering urban drainage networks (UDN), wastewate... more Integrated control of urban drainage systems considering urban drainage networks (UDN), wastewater treatment plants (WWTP) and the receiving environment seeks to minimize the impact of combined sewer overflow (CSO) to the receiving environment during wet weather. This paper will show first results of the integrated control of UDN and WWTP, obtained by LIFE-EFFIDRAIN, which is a collaborative project between academia and industry in Barcelona (Spain) and Bordeaux (France). Model predictive control (MPC) is applied for strategy optimization using conceptual hydraulic and quality variables, where the total suspended solid (TSS) concentration is selected as a representive of water quality. SWMM5 integrated with a lumped conceptual model of TSS (SWMM-TSS) is applied as virtual reality. The Perinot sewer network from Bordeaux is used as a case study for functional demonstration.

Computers & Chemical Engineering, Jun 1, 2021

Abstract Large-scale control systems tend to present a large number of alternative and back-up el... more Abstract Large-scale control systems tend to present a large number of alternative and back-up elements that, although not used in nominal operation, could be brought into play if necessary. Such hardware redundancy extends the fault tolerant capabilities of the system, while posing the problem of selecting the most suitable new system configuration. Accordingly, this paper aims to formulate the problem of, after a fault occurrence, selecting the (in some sense) optimal system configuration that maintains an admissible system performance until the restoration of the nominal service. The configuration selection is posed as a multi-objective mixed-integer program (MIP) solved using a lexicographic approach. Aiming at reducing the worst-case execution time, the analysis of necessary properties for the existence of an admissible solution, as well as how to manage the information obtained by evaluating such properties to be included in the MIP, are investigated. A portion of a water distribution network is used in order to validate the proposed solution.

IEEE Transactions on Control Systems and Technology, 2023

Model predictive control (MPC) can be used to manage combined urban drainage systems more efficie... more Model predictive control (MPC) can be used to manage combined urban drainage systems more efficiently for protection of human health and the environment, but examples of operational implementations are rare. This paper reviews more than 30 years of partly heterogeneous research on the topic. We propose a terminology for MPC of urban drainage systems and a hierarchical categorization where we emphasize four overall components: the "receding horizon principle", the "optimization model", the "optimization solver", and the "internal MPC model". Most of the reported optimization models share the trait of a multiobjective optimization based on a conceptual internal MPC model. However, there is a large variety of both convex and non-linear optimization models and optimization solvers as well as constructions of the internal MPC model. Furthermore, literature disagrees about the optimal length of the components in the receding horizon principle. The large number of MPC formulations and evaluation approaches makes it problematic to compare different MPC methods. This review highlights methods, challenges, and research gaps in order to make MPC of urban drainage systems accessible for researchers and practitioners from different disciplines. This will pave the way for shared understanding and further development within the field, and eventually lead to more operational implementations.

Annual Reviews in Control, 2023

IFAC-PapersOnLine, 2018

One of the relevant information provided by the prognostics and health management algorithms is t... more One of the relevant information provided by the prognostics and health management algorithms is the estimation of the Remaining Useful Life (RUL). The prediction of the expected RUL is very useful to decrease maintenance cost, operational downtime and safety hazards. This paper proposes a new strategy of health-aware Model Predictive Control (MPC) for a Linear Parameter Varying (LPV) system that includes as an additional goal extending the system RUL via their estimation using reliability tools. In this approach, the RUL maximization is included in the objective function of the LPV-MPC controller. The RUL is included in the MPC model as an extra parameter varying equation that considers the control action as scheduling variable. The proposed control approach allows the controller to accommodate to the parameter changes. Through computing an estimation of the state variables during prediction, the MPC model can be modified to the estimated state evolution at each time instant. Moreover, for solving the optimization problem by using a series of Quadratic Programs (QP) in each time instant, a new iterative approach is exhibited, which improves the computational efficiency. A pasteurization plant control system is used as a case study to illustrate the performance of the proposed approach.

Procedia Engineering, 2015

This paper describes an integrated model-based monitoring framework for leakage localization in d... more This paper describes an integrated model-based monitoring framework for leakage localization in district-metered areas (DMA) of water distribution networks, which takes advantage of the availability of a hydraulic model of the network. The leakage localization methodology is based on the use of flow and pressure sensors at the DMA inlets and a limited number of pressure sensors deployed inside the DMA. The placement of these sensors has been computed using an optimal sensor placement method based on a Genetic Algorithm optimization, which integrates the direct modelling approach (simulation) used to identify the location of leaks. The application of the resulting monitoring framework in a certain DMA of the Barcelona distribution network is provided and discussed using simulated leakage scenarios. The obtained results show that leakage detection and localization may be performed efficiently, reducing the required time for detection/localization, by following a simple procedure.

Journal of Water Resources Planning and Management, 2023

This article presents a novel response methodology for the operational recovery of a drinking wat... more This article presents a novel response methodology for the operational recovery of a drinking water network after an incident causes an interruption of service. The proposed optimization-based methodology allows computing the optimal set of interventions to be performed in order to mitigate, or even prevent, the impact of the incident on the network operation. Besides, a proof-of-concept scheme has been designed for the automatic generation of failure scenarios and the systematic implementation and validation of the proposed response methodology. Several results are presented to demonstrate the capability of the methodology to mitigate harmful incidents, as well as the performance improvements derived from the application of the obtained interventions.

Proceedings of the 39th IAHR World Congress, 2022

IFAC-PapersOnLine, 2015

In order to take into account the scarcity of the water resource and the increasing of the popula... more In order to take into account the scarcity of the water resource and the increasing of the population, the management of drinking water networks has to be improved with the use of new tools and actions that allows fighting against wasting water. The monitoring of drinking water networks is based on the use of sensors to locate malfunctions (leaks, quality/contamination events, etc.). Practical implementation has to be carried out by optimizing the placement of the number of sensors and improving the detection and localization of malfunctions. Techniques for the detection and localization of leaks have been proposed in the last years based on the evaluation of residuals obtained by means of the comparison between the measurements obtained by the sensors and the values obtained by simulating the water network in a leak free scenario. In this paper, a data-driven approach based on the use of statistical classifiers working in the residual space is proposed for leak localization. The classifiers are trained using leak data scenarios in all the nodes of the network considering uncertainty in demand distribution, additive noise in sensors and leak magnitude. Finally, the proposed approach is tested using the well-known Hanoi network benchmark.