Ponències/Comunicacions de congressos
http://hdl.handle.net/2117/2254
20170326T01:33:26Z

Uncertainty effect on leak localisation in a DMA
http://hdl.handle.net/2117/101541
Uncertainty effect on leak localisation in a DMA
Pérez Magrané, Ramon; Cugueró Escofet, Josep; Blesa Izquierdo, Joaquim; Cugueró, Miquel Àngel; Sanz, Gerard
The leak localisation methodologies based on data and models are affected by both uncertainties in the model and in the measurements. This uncertainty should be quantified so that its effect on the localisation methods performance can be estimated. In this paper, a modelbased leak localisation methodology is applied to a real District Metered Area using synthetic data. In the generation process of the data, uncertainty in demands is taken into account. This uncertainty was estimated so that it can justify the uncertainty observed in the real measurements. The leak localisation methodology consists, first, in generating the set of possible measurements, obtained by Monte Carlo Simulation under a certain leak assumption and considering uncertainty, and second, in falsifying sets of nodes using the correlation with a leak residual model in order to signal a set of possible leaky nodes. The assessment is done by means of generating the confusion matrix with a Monte Carlo approach.
20170224T13:04:43Z
Pérez Magrané, Ramon
Cugueró Escofet, Josep
Blesa Izquierdo, Joaquim
Cugueró, Miquel Àngel
Sanz, Gerard
The leak localisation methodologies based on data and models are affected by both uncertainties in the model and in the measurements. This uncertainty should be quantified so that its effect on the localisation methods performance can be estimated. In this paper, a modelbased leak localisation methodology is applied to a real District Metered Area using synthetic data. In the generation process of the data, uncertainty in demands is taken into account. This uncertainty was estimated so that it can justify the uncertainty observed in the real measurements. The leak localisation methodology consists, first, in generating the set of possible measurements, obtained by Monte Carlo Simulation under a certain leak assumption and considering uncertainty, and second, in falsifying sets of nodes using the correlation with a leak residual model in order to signal a set of possible leaky nodes. The assessment is done by means of generating the confusion matrix with a Monte Carlo approach.

Faulttolerant periodic economic model predictive control of differentialalgebraicequation systems
http://hdl.handle.net/2117/101314
Faulttolerant periodic economic model predictive control of differentialalgebraicequation systems
Wang, Ye; Puig Cayuela, Vicenç; Cembrano Gennari, Gabriela
This paper addresses a faulttolerant periodic economic model predictive control (MPC) strategy for differentialalgebraicequation (DAE) systems. Fault tolerance evaluation of the proposed economic MPC strategy uses set computations and a performance degradation analysis. By means of the set computations, the feasible solution set (including system states and control inputs) can be determined as well as the admissible performance set can be obtained when system reconfiguration or fault accommodation strategies are used. The proposed control strategy allows to carry out an analysis of performance degradation by using the feasible and admissible performance set. As a result, if the performance degradation is accepted, the economic MPC controller can be applied using system reconfiguration or fault accommodation. Finally, the proposed faulttolerant MPC strategy is verified through an illustrative example.
© 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
20170221T12:46:09Z
Wang, Ye
Puig Cayuela, Vicenç
Cembrano Gennari, Gabriela
This paper addresses a faulttolerant periodic economic model predictive control (MPC) strategy for differentialalgebraicequation (DAE) systems. Fault tolerance evaluation of the proposed economic MPC strategy uses set computations and a performance degradation analysis. By means of the set computations, the feasible solution set (including system states and control inputs) can be determined as well as the admissible performance set can be obtained when system reconfiguration or fault accommodation strategies are used. The proposed control strategy allows to carry out an analysis of performance degradation by using the feasible and admissible performance set. As a result, if the performance degradation is accepted, the economic MPC controller can be applied using system reconfiguration or fault accommodation. Finally, the proposed faulttolerant MPC strategy is verified through an illustrative example.

Guaranteed state estimation and fault detection based on zonotopes for differentialalgebraicequation systems
http://hdl.handle.net/2117/101306
Guaranteed state estimation and fault detection based on zonotopes for differentialalgebraicequation systems
Wang, Ye; Puig Cayuela, Vicenç; Cembrano Gennari, Gabriela; Álamo, Teodoro
This paper presents a setmembership approach based on zonotopes for differentialalgebraicequation (DAE) systems with unknownbutbounded disturbances and noise, which can be subsequently used for guaranteed state estimation and fault detection. Complex systems are usually modeled by differential and algebraic equations, where differential equations describe system dynamics and additionally, algebraic equations represent the static relations. The proposed algorithm provides a way to propagate a zonotopic set that contains the system states not only consistent with the measurement outputs but also constrained with their static relations. Finally, a real application has been presented to verify the proposed approach.
© 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
20170221T11:47:34Z
Wang, Ye
Puig Cayuela, Vicenç
Cembrano Gennari, Gabriela
Álamo, Teodoro
This paper presents a setmembership approach based on zonotopes for differentialalgebraicequation (DAE) systems with unknownbutbounded disturbances and noise, which can be subsequently used for guaranteed state estimation and fault detection. Complex systems are usually modeled by differential and algebraic equations, where differential equations describe system dynamics and additionally, algebraic equations represent the static relations. The proposed algorithm provides a way to propagate a zonotopic set that contains the system states not only consistent with the measurement outputs but also constrained with their static relations. Finally, a real application has been presented to verify the proposed approach.

Leak localization in water distribution networks using modelbased bayesian reasoning
http://hdl.handle.net/2117/101117
Leak localization in water distribution networks using modelbased bayesian reasoning
Soldevila Coma, Adrià; Fernández Canti, Rosa M.; Blesa Izquierdo, Joaquim; Tornil Sin, Sebastián; Puig Cayuela, Vicenç
This paper presents a new method for leak localization in Water Distribution Networks that uses a modelbased approach combined with Bayesian reasoning. Probability density functions in modelbased pressure residuals are calibrated offline for all the possible leak scenarios by using a hydraulic simulator, being leak size uncertainty, demand uncertainty and sensor noise considered. A Bayesian reasoning is applied online to the available residuals to determine the location of leaks present in the Water Distribution Network. A time horizon method combined with the Bayesian reasoning is also proposed to improve the accuracy of the leak localization method. The Hanoi District Metered Area case study is used to illustrate the performance of the proposed approach.
20170215T16:51:10Z
Soldevila Coma, Adrià
Fernández Canti, Rosa M.
Blesa Izquierdo, Joaquim
Tornil Sin, Sebastián
Puig Cayuela, Vicenç
This paper presents a new method for leak localization in Water Distribution Networks that uses a modelbased approach combined with Bayesian reasoning. Probability density functions in modelbased pressure residuals are calibrated offline for all the possible leak scenarios by using a hydraulic simulator, being leak size uncertainty, demand uncertainty and sensor noise considered. A Bayesian reasoning is applied online to the available residuals to determine the location of leaks present in the Water Distribution Network. A time horizon method combined with the Bayesian reasoning is also proposed to improve the accuracy of the leak localization method. The Hanoi District Metered Area case study is used to illustrate the performance of the proposed approach.

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.

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.

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.

HRA*: hybrid randomized path planning for complex 3D environments
http://hdl.handle.net/2117/89386
HRA*: hybrid randomized path planning for complex 3D environments
Teniente Avilés, Ernesto Homar; AndradeCetto, Juan
We propose HRA*, a new randomized path planner for complex 3D environments. The method is a modified A* algorithm that uses a hybrid node expansion technique that combines a random exploration of the action space meeting vehicle kinematic constraints with a cost to goal metric that considers only kinematically feasible paths to the goal. The method includes also a series of heuristics to accelerate the search time. These include a cost penalty near obstacles, and a filter to prevent revisiting configurations. The performance of the method is compared against A*, RRT and RRT* in a series of challenging 3D outdoor datasets. HRA* is shown to outperform all of them in computation time, and delivering shorter paths than A* and RR
20160826T10:14:58Z
Teniente Avilés, Ernesto Homar
AndradeCetto, Juan
We propose HRA*, a new randomized path planner for complex 3D environments. The method is a modified A* algorithm that uses a hybrid node expansion technique that combines a random exploration of the action space meeting vehicle kinematic constraints with a cost to goal metric that considers only kinematically feasible paths to the goal. The method includes also a series of heuristics to accelerate the search time. These include a cost penalty near obstacles, and a filter to prevent revisiting configurations. The performance of the method is compared against A*, RRT and RRT* in a series of challenging 3D outdoor datasets. HRA* is shown to outperform all of them in computation time, and delivering shorter paths than A* and RR