Ponències/Comunicacions de congressos
http://hdl.handle.net/2117/1126
20170123T12:55:58Z

Flow meter data validation and reconstruction using neural networks: Application to the Barcelona water network
http://hdl.handle.net/2117/99695
Flow meter data validation and reconstruction using neural networks: Application to the Barcelona water network
Rodríguez, Héctor; Puig Cayuela, Vicenç; Flores, Juan; López, Rodrigo
The use of false or erroneous data can lead to wrong decisions when operating a system. In case of a water distribution network, the use of incorrect data could lead to errors in the billing system, waste of energy, incorrect management of control elements, etc. This paper is focused on detecting Flow meters reading abnormalities by exploiting the temporal redundancy of the demand time series by means of artificial neural networks (ANN). Communication problems with the sensor generate missing data and bad maintenanceservice in the flow meters produce false data. In this work, a methodology to detect the false data (validate) and replace the missing or false data (reconstruct) is proposed. As a core methodology, ANNs are used to model the time series generated from the water demand flow meters, and use the confidence intervals to validate the information. To illustrate the proposed methodology, the application to flow meters in the water distribution network of Barcelona is used.
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
20170119T13:47:12Z
Rodríguez, Héctor
Puig Cayuela, Vicenç
Flores, Juan
López, Rodrigo
The use of false or erroneous data can lead to wrong decisions when operating a system. In case of a water distribution network, the use of incorrect data could lead to errors in the billing system, waste of energy, incorrect management of control elements, etc. This paper is focused on detecting Flow meters reading abnormalities by exploiting the temporal redundancy of the demand time series by means of artificial neural networks (ANN). Communication problems with the sensor generate missing data and bad maintenanceservice in the flow meters produce false data. In this work, a methodology to detect the false data (validate) and replace the missing or false data (reconstruct) is proposed. As a core methodology, ANNs are used to model the time series generated from the water demand flow meters, and use the confidence intervals to validate the information. To illustrate the proposed methodology, the application to flow meters in the water distribution network of Barcelona is used.

Decentralized fault diagnosis using analytical redundancy relations: Application to a water distribution network
http://hdl.handle.net/2117/99693
Decentralized fault diagnosis using analytical redundancy relations: Application to a water distribution network
Gupta, Vikas; Puig Cayuela, Vicenç
In this paper, a decentralized fault diagnosis algorithm for large scale systems is proposed. The fault diagnosis algorithm starts with obtaining a set of ARRs (analytical redundancy relations) from the system model and available sensors. These ARRs are converted into a graph that is divided into various subgraphs using a partition algorithm. From various subgraphs, different fault signature matrices are obtained. This allows designing a decentralized fault diagnosis system by using a local diagnoser for each subsystem and a global one for coordination. Entire proposed decentralized fault diagnosis algorithm is divided into five different blocks. In order to illustratethe application of the proposed algorithm, a casestudy based on the Barcelona water network is used.
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
20170119T13:39:47Z
Gupta, Vikas
Puig Cayuela, Vicenç
In this paper, a decentralized fault diagnosis algorithm for large scale systems is proposed. The fault diagnosis algorithm starts with obtaining a set of ARRs (analytical redundancy relations) from the system model and available sensors. These ARRs are converted into a graph that is divided into various subgraphs using a partition algorithm. From various subgraphs, different fault signature matrices are obtained. This allows designing a decentralized fault diagnosis system by using a local diagnoser for each subsystem and a global one for coordination. Entire proposed decentralized fault diagnosis algorithm is divided into five different blocks. In order to illustratethe application of the proposed algorithm, a casestudy based on the Barcelona water network is used.

Economic MPC with periodic terminal constraints of nonlinear differentialalgebraicequation systems: Application to drinking water networks
http://hdl.handle.net/2117/99463
Economic MPC with periodic terminal constraints of nonlinear differentialalgebraicequation systems: Application to drinking water networks
Wang, Ye; Puig Cayuela, Vicenç; Cembrano Gennari, Gabriela
In this paper, an Economic Model Predictive Control (EMPC) strategy with periodic terminal constraints is addressed for nonlinear differentialalgebraicequation systems with an application to Drinking Water Networks (DWNs). DWNs have some periodic behaviours because of the daily seasonality of water demands and electrical energy price. The periodic terminal constraint and economic terminal cost are implemented in the EMPC controller design for the purpose of
achieving convergence. The feasibility of the proposed EMPC strategy when disturbances are considered is guaranteed by means of soft constraints implemented by using slack variables.
Finally, the comparison results in a case study of the DTown water network is provided by applying the EMPC strategy with or without periodic terminal constraints.
© 2026 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
20170117T12:59:31Z
Wang, Ye
Puig Cayuela, Vicenç
Cembrano Gennari, Gabriela
In this paper, an Economic Model Predictive Control (EMPC) strategy with periodic terminal constraints is addressed for nonlinear differentialalgebraicequation systems with an application to Drinking Water Networks (DWNs). DWNs have some periodic behaviours because of the daily seasonality of water demands and electrical energy price. The periodic terminal constraint and economic terminal cost are implemented in the EMPC controller design for the purpose of
achieving convergence. The feasibility of the proposed EMPC strategy when disturbances are considered is guaranteed by means of soft constraints implemented by using slack variables.
Finally, the comparison results in a case study of the DTown water network is provided by applying the EMPC strategy with or without periodic terminal constraints.

Sensor placement algorithm for distributed fault diagnosis
http://hdl.handle.net/2117/99444
Sensor placement algorithm for distributed fault diagnosis
Gupta, Vikas; Puig Cayuela, Vicenç
In this paper, an algorithm for sensor placement for distributed fault diagnosis is proposed. The main objective of this algorithm is to place the sensors in a system in such a manner that the partition of a system into
various subsystems becomes easier facilitating the implementation of a distributed fault diagnosis system. This algorithm also reduces or minimized the number of sensors to be used or install thus reducing overall cost. Binary integer linear programming is used for optimization in this algorithm. A four water tank system has been used to demonstrate and validate the proposed algorithm.
20170117T12:19:49Z
Gupta, Vikas
Puig Cayuela, Vicenç
In this paper, an algorithm for sensor placement for distributed fault diagnosis is proposed. The main objective of this algorithm is to place the sensors in a system in such a manner that the partition of a system into
various subsystems becomes easier facilitating the implementation of a distributed fault diagnosis system. This algorithm also reduces or minimized the number of sensors to be used or install thus reducing overall cost. Binary integer linear programming is used for optimization in this algorithm. A four water tank system has been used to demonstrate and validate the proposed algorithm.

Nonlinear model predictive control with constraint satisfactions for a quadcopter
http://hdl.handle.net/2117/99393
Nonlinear model predictive control with constraint satisfactions for a quadcopter
Wang, Ye; Ramírez Jaime, Andrés Felipe; Xu, Feng; Puig Cayuela, Vicenç
This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for a quadcopter. The full dynamics of the quadcopter describing the attitude and position are nonlinear, which are quite sensitive to changes of inputs and disturbances. By means of constraint satisfactions, partial nonlinearities and modeling errors of the controloriented model of full dynamics can be transformed into the inequality constraints. Subsequently, the quadcopter can be controlled by an NMPC controller with the updated constraints generated by constraint satisfactions. Finally, the simulation results applied to a quadcopter simulator are provided to show the e ectiveness of he proposed strategy.
20170117T08:45:33Z
Wang, Ye
Ramírez Jaime, Andrés Felipe
Xu, Feng
Puig Cayuela, Vicenç
This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for a quadcopter. The full dynamics of the quadcopter describing the attitude and position are nonlinear, which are quite sensitive to changes of inputs and disturbances. By means of constraint satisfactions, partial nonlinearities and modeling errors of the controloriented model of full dynamics can be transformed into the inequality constraints. Subsequently, the quadcopter can be controlled by an NMPC controller with the updated constraints generated by constraint satisfactions. Finally, the simulation results applied to a quadcopter simulator are provided to show the e ectiveness of he proposed strategy.

Robust optimization based energy dispatch in smart grids considering demand uncertainty
http://hdl.handle.net/2117/99391
Robust optimization based energy dispatch in smart grids considering demand uncertainty
Nassourou, M; Puig Cayuela, Vicenç; Blesa Izquierdo, Joaquim
In this study we discuss the application of robust optimization to the problem of economic energy dispatch in smart grids. Robust optimization based MPC strategies for tackling uncertain load demands are developed. Unexpected additive disturbances are modelled by defining an affine dependence between the control inputs and the uncertain load demands.
The developed strategies were applied to a hybrid power system connected to an electrical power grid. Furthermore, to demonstrate the superiority of the standard Economic MPC over the MPC tracking, a comparison (e.g average daily cost) between the standard MPC tracking, the standard Economic MPC, and the integration of both in onelayer and twolayer approaches was carried out. The goal of this research is to design a controller based on Economic MPC
strategies, that tackles uncertainties, in order to minimise economic costs and guarantee service reliability of the system.
20170117T08:30:39Z
Nassourou, M
Puig Cayuela, Vicenç
Blesa Izquierdo, Joaquim
In this study we discuss the application of robust optimization to the problem of economic energy dispatch in smart grids. Robust optimization based MPC strategies for tackling uncertain load demands are developed. Unexpected additive disturbances are modelled by defining an affine dependence between the control inputs and the uncertain load demands.
The developed strategies were applied to a hybrid power system connected to an electrical power grid. Furthermore, to demonstrate the superiority of the standard Economic MPC over the MPC tracking, a comparison (e.g average daily cost) between the standard MPC tracking, the standard Economic MPC, and the integration of both in onelayer and twolayer approaches was carried out. The goal of this research is to design a controller based on Economic MPC
strategies, that tackles uncertainties, in order to minimise economic costs and guarantee service reliability of the system.

Sensor placement for leak monitoring in drinking water networks combining clustering techniques and a semiexhaustive search
http://hdl.handle.net/2117/98918
Sensor placement for leak monitoring in drinking water networks combining clustering techniques and a semiexhaustive search
Sarrate Estruch, Ramon; Blesa Izquierdo, Joaquim; Nejjari AkhiElarab, Fatiha
This paper presents an optimal sensor placement strategy based on pressure sensitivity matrix analysis
and a semiexhaustive search strategy that maximizes some diagnosis specifications for water distribution networks.
A mean average worst leak expansion distance has been proposed as a new leak location performance measure.
The approach is combined with a clustering technique in order to reduce the size and the complexity of the sensor
placement problem. The strategy is successfully applied to determine the location of a set of pressure sensors in a
district metered area (DMA) in the Barcelona water distribution network (WDN).
20170110T08:47:35Z
Sarrate Estruch, Ramon
Blesa Izquierdo, Joaquim
Nejjari AkhiElarab, Fatiha
This paper presents an optimal sensor placement strategy based on pressure sensitivity matrix analysis
and a semiexhaustive search strategy that maximizes some diagnosis specifications for water distribution networks.
A mean average worst leak expansion distance has been proposed as a new leak location performance measure.
The approach is combined with a clustering technique in order to reduce the size and the complexity of the sensor
placement problem. The strategy is successfully applied to determine the location of a set of pressure sensors in a
district metered area (DMA) in the Barcelona water distribution network (WDN).

Decentralized faulttolerant control of inland navigation networks: a challenge
http://hdl.handle.net/2117/98883
Decentralized faulttolerant control of inland navigation networks: a challenge
Segovia, Pablo; Rajaoarisoa, Lala H.; Nejjari AkhiElarab, Fatiha; Blesa Izquierdo, Joaquim; Puig Cayuela, Vicenç; Duviella, Eric
Inland waterways are largescale networks used principally for navigation. Even if the transport planning is an important issue, the water resource management is a crucial point. Indeed, navigation is
not possible when there is too little or too much water inside the waterways. Hence, the water resource management of waterways has to be particularly efficient in a context of climate change and increase of water demand. This management has to be done by considering different time and space scales and still requires the development of new methodologies and tools in the topics of the Control and Informatics communities. This work addresses the problem of waterways management in terms of modeling, control, diagnosis and faulttolerant control by focusing in the inland waterways of the north of France. A review of proposed tools and the ongoing research topics are provided in this paper.
20170109T13:28:56Z
Segovia, Pablo
Rajaoarisoa, Lala H.
Nejjari AkhiElarab, Fatiha
Blesa Izquierdo, Joaquim
Puig Cayuela, Vicenç
Duviella, Eric
Inland waterways are largescale networks used principally for navigation. Even if the transport planning is an important issue, the water resource management is a crucial point. Indeed, navigation is
not possible when there is too little or too much water inside the waterways. Hence, the water resource management of waterways has to be particularly efficient in a context of climate change and increase of water demand. This management has to be done by considering different time and space scales and still requires the development of new methodologies and tools in the topics of the Control and Informatics communities. This work addresses the problem of waterways management in terms of modeling, control, diagnosis and faulttolerant control by focusing in the inland waterways of the north of France. A review of proposed tools and the ongoing research topics are provided in this paper.

Fault detection and isolation using viability theory and interval observers
http://hdl.handle.net/2117/98854
Fault detection and isolation using viability theory and interval observers
Ghaniee Zarch, Majid; Puig Cayuela, Vicenç; Poshtan, Javad
This paper proposes the use of interval observers and viability theory in fault detection and isolation (FDI). Viability theory develops mathematical and algorithmic methods for investigating the
adaptation to viability constraints of evolutions governed by complex systems under uncertainty. These methods can be used for checking the consistency between observed and predicted behavior by using simple sets that approximate the exact set of possible behavior (in the parameter or state space). In this paper, fault detection is based on checking for an inconsistency between the measured and predicted behaviors using viability theory concepts and sets. Finally, an example is provided in order to show the usefulness of the proposed approach.
20170109T11:02:12Z
Ghaniee Zarch, Majid
Puig Cayuela, Vicenç
Poshtan, Javad
This paper proposes the use of interval observers and viability theory in fault detection and isolation (FDI). Viability theory develops mathematical and algorithmic methods for investigating the
adaptation to viability constraints of evolutions governed by complex systems under uncertainty. These methods can be used for checking the consistency between observed and predicted behavior by using simple sets that approximate the exact set of possible behavior (in the parameter or state space). In this paper, fault detection is based on checking for an inconsistency between the measured and predicted behaviors using viability theory concepts and sets. Finally, an example is provided in order to show the usefulness of the proposed approach.

A methodology for distributed fault diagnosis
http://hdl.handle.net/2117/98843
A methodology for distributed fault diagnosis
Gupta, Vikas; Puig Cayuela, Vicenç; Blesa Izquierdo, Joaquim
In this paper, a methodology for distributed fault diagnosis is proposed. The algorithm places the sensors in a system in such a manner that the partition of a system into various subsystems becomes easier facilitating the implementation of a distributed fault diagnosis system. This algorithm also reduces or minimized the number of sensors to be used or install thus reducing overall cost. Binary integer linear programming is used for optimization in this algorithm. Real case study of Barcelona wat
er network has been used to demonstrate and validate the proposed algorithm.
20170109T10:25:42Z
Gupta, Vikas
Puig Cayuela, Vicenç
Blesa Izquierdo, Joaquim
In this paper, a methodology for distributed fault diagnosis is proposed. The algorithm places the sensors in a system in such a manner that the partition of a system into various subsystems becomes easier facilitating the implementation of a distributed fault diagnosis system. This algorithm also reduces or minimized the number of sensors to be used or install thus reducing overall cost. Binary integer linear programming is used for optimization in this algorithm. Real case study of Barcelona wat
er network has been used to demonstrate and validate the proposed algorithm.