Ponències/Comunicacions de congressos
http://hdl.handle.net/2117/1126
Thu, 19 Jan 2017 02:15:47 GMT
20170119T02:15:47Z

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.
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Tue, 17 Jan 2017 12:59:31 GMT
http://hdl.handle.net/2117/99463
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.
Tue, 17 Jan 2017 12:19:49 GMT
http://hdl.handle.net/2117/99444
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.
Tue, 17 Jan 2017 08:45:33 GMT
http://hdl.handle.net/2117/99393
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.
Tue, 17 Jan 2017 08:30:39 GMT
http://hdl.handle.net/2117/99391
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).
Tue, 10 Jan 2017 08:47:35 GMT
http://hdl.handle.net/2117/98918
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.
Mon, 09 Jan 2017 13:28:56 GMT
http://hdl.handle.net/2117/98883
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.
Mon, 09 Jan 2017 11:02:12 GMT
http://hdl.handle.net/2117/98854
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.
Mon, 09 Jan 2017 10:25:42 GMT
http://hdl.handle.net/2117/98843
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.

Healthaware model predictive control of pasteurization plant
http://hdl.handle.net/2117/98842
Healthaware model predictive control of pasteurization plant
Karimi Pour, F.; Puig Cayuela, Vicenç; OcampoMartínez, Carlos
In order to optimize the tradeoff between components life and energy consumption, the integration of a system health management and control modules is required. This paper proposes the integration of model predictive control (MPC) with a fatigue estimation approach that minimizes the damage of the components of a pasteurization plant. The fatigue estimation is assessed with the rainflow counting algorithm. Using data from this algorithm, a simplified model that characterizes the health of the system is developed and integrated with MPC. The MPC controller objective is modified by adding an extra criterion that takes into account the accumulated damage. But, a steadystate offset is created by adding this extra criterion. Finally, by including an integral action in the MPC controller, the steadystate error for regulation purpose is eliminated. The proposed control scheme is validated in simulation using a simulator of a utilityscale pasteurization plant.
Mon, 09 Jan 2017 10:21:01 GMT
http://hdl.handle.net/2117/98842
20170109T10:21:01Z
Karimi Pour, F.
Puig Cayuela, Vicenç
OcampoMartínez, Carlos
In order to optimize the tradeoff between components life and energy consumption, the integration of a system health management and control modules is required. This paper proposes the integration of model predictive control (MPC) with a fatigue estimation approach that minimizes the damage of the components of a pasteurization plant. The fatigue estimation is assessed with the rainflow counting algorithm. Using data from this algorithm, a simplified model that characterizes the health of the system is developed and integrated with MPC. The MPC controller objective is modified by adding an extra criterion that takes into account the accumulated damage. But, a steadystate offset is created by adding this extra criterion. Finally, by including an integral action in the MPC controller, the steadystate error for regulation purpose is eliminated. The proposed control scheme is validated in simulation using a simulator of a utilityscale pasteurization plant.

State and fault estimation in singular delayed LPV systems
http://hdl.handle.net/2117/97754
State and fault estimation in singular delayed LPV systems
Hassanabadi, Amir Hossein; Shafiee, Masoud; Puig Cayuela, Vicenç
In this paper, the state and fault estimation problem of singular delayed LPV systems in the presence of disturbances and actuator faults is considered. The system under consideration has multiple unknown time varying delays. For both state and actuator fault estimation, an Unknown Input Observer (UIO) is proposed. Robustness to unknown inputs and uncertainty induced by unknown delays is formulated by means of the Bounded Real Lemma (BRL) for delayed LPV systems. UIO design procedure with a certain level of unknown input attenuation is formulated using LMIs. Also the best achievable attenuation level is computed in a convex optimization framework with LMI constraints. The efficiency of the proposed approach is illustrated via a numerical example.
Mon, 05 Dec 2016 10:37:14 GMT
http://hdl.handle.net/2117/97754
20161205T10:37:14Z
Hassanabadi, Amir Hossein
Shafiee, Masoud
Puig Cayuela, Vicenç
In this paper, the state and fault estimation problem of singular delayed LPV systems in the presence of disturbances and actuator faults is considered. The system under consideration has multiple unknown time varying delays. For both state and actuator fault estimation, an Unknown Input Observer (UIO) is proposed. Robustness to unknown inputs and uncertainty induced by unknown delays is formulated by means of the Bounded Real Lemma (BRL) for delayed LPV systems. UIO design procedure with a certain level of unknown input attenuation is formulated using LMIs. Also the best achievable attenuation level is computed in a convex optimization framework with LMI constraints. The efficiency of the proposed approach is illustrated via a numerical example.