Articles de revista
http://hdl.handle.net/2117/1125
Tue, 21 Nov 2017 06:12:38 GMT
20171121T06:12:38Z

A distributed predictive control approach for periodic flowbased networks: application to drinking water systems
http://hdl.handle.net/2117/110930
A distributed predictive control approach for periodic flowbased networks: application to drinking water systems
Grosso Perez, Juan Manuel; OcampoMartínez, Carlos; Puig Cayuela, Vicenç
This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flowbased networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (alltoall) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of nonsparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a largescale complex flowbased network: the Barcelona drinking water supply system.
Mon, 20 Nov 2017 15:30:05 GMT
http://hdl.handle.net/2117/110930
20171120T15:30:05Z
Grosso Perez, Juan Manuel
OcampoMartínez, Carlos
Puig Cayuela, Vicenç
This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flowbased networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (alltoall) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of nonsparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a largescale complex flowbased network: the Barcelona drinking water supply system.

Leak localization in water distribution networks using Bayesian classifiers
http://hdl.handle.net/2117/110151
Leak localization in water distribution networks using Bayesian classifiers
Soldevila Coma, Adrià; Fernández Canti, Rosa M.; Blesa Izquierdo, Joaquim; Tornil Sin, Sebastián; Puig Cayuela, Vicenç
This paper presents a method for leak localization in water distribution networks (WDNs) based on Bayesian classifiers. Probability density functions for pressure residuals are calibrated offline for all the possible leak scenarios by using a hydraulic simulator, and considering the leak size uncertainty, demand uncertainty and sensor noise. A Bayesian classifier is applied online to the computed residuals to determine the location of leaks in the WDN. A time horizon based reasoning combined with the Bayesian classifier is also proposed to improve the localization accuracy. Two case studies based on the Hanoi and the Nova Icària networks are used to illustrate the performance of the proposed approach. Simulation results are presented for the Hanoi case study, whereas results for a real leak scenario are shown for the Nova Icària case study.
Wed, 08 Nov 2017 14:00:50 GMT
http://hdl.handle.net/2117/110151
20171108T14:00:50Z
Soldevila Coma, Adrià
Fernández Canti, Rosa M.
Blesa Izquierdo, Joaquim
Tornil Sin, Sebastián
Puig Cayuela, Vicenç
This paper presents a method for leak localization in water distribution networks (WDNs) based on Bayesian classifiers. Probability density functions for pressure residuals are calibrated offline for all the possible leak scenarios by using a hydraulic simulator, and considering the leak size uncertainty, demand uncertainty and sensor noise. A Bayesian classifier is applied online to the computed residuals to determine the location of leaks in the WDN. A time horizon based reasoning combined with the Bayesian classifier is also proposed to improve the localization accuracy. Two case studies based on the Hanoi and the Nova Icària networks are used to illustrate the performance of the proposed approach. Simulation results are presented for the Hanoi case study, whereas results for a real leak scenario are shown for the Nova Icària case study.

Distributed zonotopic setmembership state estimation based on optimization methods with partial projection
http://hdl.handle.net/2117/110150
Distributed zonotopic setmembership state estimation based on optimization methods with partial projection
Álamo Cantarero, Teodoro; Wang, Ye; Puig Cayuela, Vicenç; Cembrano Gennari, Gabriela
A distributed setmembership 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 unknownbutbounded system disturbances and measurement noise. In the framework of the setmembership 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 2norm criterion of the generator matrix. Meanwhile, for the distributed setmembership estimators, the partial projection method is considered to correct the estimation of the neighbor state. On the other hand, an online method is also provided. Finally, the proposed distributed setmembership approach is verified in a case study based on a urban drainage network.
Wed, 08 Nov 2017 13:57:33 GMT
http://hdl.handle.net/2117/110150
20171108T13:57:33Z
Álamo Cantarero, Teodoro
Wang, Ye
Puig Cayuela, Vicenç
Cembrano Gennari, Gabriela
A distributed setmembership 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 unknownbutbounded system disturbances and measurement noise. In the framework of the setmembership 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 2norm criterion of the generator matrix. Meanwhile, for the distributed setmembership estimators, the partial projection method is considered to correct the estimation of the neighbor state. On the other hand, an online method is also provided. Finally, the proposed distributed setmembership approach is verified in a case study based on a urban drainage network.

Solving Diagnosability of Hybrid Systems via Abstraction and Discrete Event Techniques
http://hdl.handle.net/2117/110149
Solving Diagnosability of Hybrid Systems via Abstraction and Discrete Event Techniques
Grastien, Alban; TravéMassuyès, Louise; Puig Cayuela, Vicenç
This paper addresses the problem of determining the diagnosability of hybrid systems by abstracting hybrid models to a discrete event setting. From the continuous model the abstraction only remembers two pieces of information: indiscernability between modes (when they are guaranteed to generate different observations) and ephemerality (when the system cannot stay forever in a given set of modes). Then, we use standard discrete event system diagnosability algorithms. The second contribution is an iterative approach to diagnosability that starts from the most abstract discrete event model of the hybrid system. If it is diagnosable, that means that the hybrid system is diagnosable. If it is not, the counterexample generated by the diagnosability procedure is analysed to refine the DES. If no refinement is found, then it can not be proved that the hybrid system is diagnosable. Otherwise, the refinement is included in the abstract DES model and the diagnosability procedure continues.
Wed, 08 Nov 2017 13:26:25 GMT
http://hdl.handle.net/2117/110149
20171108T13:26:25Z
Grastien, Alban
TravéMassuyès, Louise
Puig Cayuela, Vicenç
This paper addresses the problem of determining the diagnosability of hybrid systems by abstracting hybrid models to a discrete event setting. From the continuous model the abstraction only remembers two pieces of information: indiscernability between modes (when they are guaranteed to generate different observations) and ephemerality (when the system cannot stay forever in a given set of modes). Then, we use standard discrete event system diagnosability algorithms. The second contribution is an iterative approach to diagnosability that starts from the most abstract discrete event model of the hybrid system. If it is diagnosable, that means that the hybrid system is diagnosable. If it is not, the counterexample generated by the diagnosability procedure is analysed to refine the DES. If no refinement is found, then it can not be proved that the hybrid system is diagnosable. Otherwise, the refinement is included in the abstract DES model and the diagnosability procedure continues.

Iterative learning control experimental results in twinrotor device
http://hdl.handle.net/2117/110132
Iterative learning control experimental results in twinrotor device
Mascaró Palliser, Ruben; Costa Castelló, Ramon; Ramos Fuentes, German A.
This paper presents the results of applying the Iterative Learning Control algorithms to a TwinRotor MultipleInput MultipleOutput System (TRMS) in order to achieve high performance in repetitive tracking of trajectories. The plant, which is similar to a prototype of helicopter, is characterized by its highly nonlinear and crosscoupled dynamics. In the first phase, the system is modelled using the Lagrangian approach and combining theoretical and experimental results. Thereafter, a hierarchical control architecture which combines a baseline feedback controller with an Iterative Learning Control algorithm is developed. Finally, the responses of the real device and a complete analysis of the learning behaviour are exposed.
Wed, 08 Nov 2017 09:59:13 GMT
http://hdl.handle.net/2117/110132
20171108T09:59:13Z
Mascaró Palliser, Ruben
Costa Castelló, Ramon
Ramos Fuentes, German A.
This paper presents the results of applying the Iterative Learning Control algorithms to a TwinRotor MultipleInput MultipleOutput System (TRMS) in order to achieve high performance in repetitive tracking of trajectories. The plant, which is similar to a prototype of helicopter, is characterized by its highly nonlinear and crosscoupled dynamics. In the first phase, the system is modelled using the Lagrangian approach and combining theoretical and experimental results. Thereafter, a hierarchical control architecture which combines a baseline feedback controller with an Iterative Learning Control algorithm is developed. Finally, the responses of the real device and a complete analysis of the learning behaviour are exposed.

Temperature control of opencathode PEM fuel cells
http://hdl.handle.net/2117/110131
Temperature control of opencathode PEM fuel cells
Strahl, Stephan; Costa Castelló, Ramon
Proper temperature control of Proton Exchange Membrane (PEM) Fuel Cells is a crucial factor for optimizing fuel cell performance. A robust temperature controller is required for optimal water management of PEM fuel cells. This paper describes a modelbased characterization of the equilibrium points of an opencathode fuel cell system as the baseline for proper controller design, highlighting the relation between fuel cell temperature, humidification and performance. Phase plane analysis of the nonlinear model versus a linearized model around different points of operation shows the potential of approximating the nonlinear system behavior with a linear model. The methodology for the system analysis presented in this paper finally serves for the development of control schemes using robust control techniques. The designed controller is validated in simulation with the nonlinear plant model.
Wed, 08 Nov 2017 09:26:32 GMT
http://hdl.handle.net/2117/110131
20171108T09:26:32Z
Strahl, Stephan
Costa Castelló, Ramon
Proper temperature control of Proton Exchange Membrane (PEM) Fuel Cells is a crucial factor for optimizing fuel cell performance. A robust temperature controller is required for optimal water management of PEM fuel cells. This paper describes a modelbased characterization of the equilibrium points of an opencathode fuel cell system as the baseline for proper controller design, highlighting the relation between fuel cell temperature, humidification and performance. Phase plane analysis of the nonlinear model versus a linearized model around different points of operation shows the potential of approximating the nonlinear system behavior with a linear model. The methodology for the system analysis presented in this paper finally serves for the development of control schemes using robust control techniques. The designed controller is validated in simulation with the nonlinear plant model.

Noncentralized control for flowbased distribution networks: a gametheoretical insight
http://hdl.handle.net/2117/109821
Noncentralized control for flowbased distribution networks: a gametheoretical insight
Barreiro Gómez, Julian; OcampoMartínez, Carlos; Quijano Silva, Nicanor; Maestre Torreblanca, José María
This paper solves a datadriven control problem for a flowbased distribution network with two objectives: a resource allocation and a fair distribution of costs. These objectives represent both cooperation and competition directions. It is proposed a solution that combines either a centralized or distributed cooperative game approach using the Shapley value to determine a proper partitioning of the system and a fair communication cost distribution. On the other hand, a decentralized noncooperative game approach computing the Nash equilibrium is used to achieve the control objective of the resource allocation under a noncomplete information topology. Furthermore, an invariantset property is presented and the closedloop system stability is analyzed for the noncooperative game approach. Another contribution regarding the cooperative game approach is an alternative way to compute the Shapley value for the proposed specific characteristic function. Unlike the classical cooperativegames approach, which has a limited application due to the combinatorial explosion issues, the alternative method allows calculating the Shapley value in polynomial time and hence can be applied to largescale problems.
© <year>. This manuscript version is made available under the CCBYNCND 4.0 license http://creativecommons.org/licenses/byncnd/4.0/
Mon, 06 Nov 2017 08:55:03 GMT
http://hdl.handle.net/2117/109821
20171106T08:55:03Z
Barreiro Gómez, Julian
OcampoMartínez, Carlos
Quijano Silva, Nicanor
Maestre Torreblanca, José María
This paper solves a datadriven control problem for a flowbased distribution network with two objectives: a resource allocation and a fair distribution of costs. These objectives represent both cooperation and competition directions. It is proposed a solution that combines either a centralized or distributed cooperative game approach using the Shapley value to determine a proper partitioning of the system and a fair communication cost distribution. On the other hand, a decentralized noncooperative game approach computing the Nash equilibrium is used to achieve the control objective of the resource allocation under a noncomplete information topology. Furthermore, an invariantset property is presented and the closedloop system stability is analyzed for the noncooperative game approach. Another contribution regarding the cooperative game approach is an alternative way to compute the Shapley value for the proposed specific characteristic function. Unlike the classical cooperativegames approach, which has a limited application due to the combinatorial explosion issues, the alternative method allows calculating the Shapley value in polynomial time and hence can be applied to largescale problems.

New approach to ball mill modelling as a piston flow process
http://hdl.handle.net/2117/109155
New approach to ball mill modelling as a piston flow process
Guasch Cascalló, Eduard; Anticoi Sudzuki, Hernán Francisco; Hamid, Sarbast; Oliva Moncunill, Josep; Alfonso Abella, María Pura; Escobet Canal, Teresa; Sanmiquel Pera, Lluís; Bascompta Massanes, Marc
Wed, 25 Oct 2017 12:29:34 GMT
http://hdl.handle.net/2117/109155
20171025T12:29:34Z
Guasch Cascalló, Eduard
Anticoi Sudzuki, Hernán Francisco
Hamid, Sarbast
Oliva Moncunill, Josep
Alfonso Abella, María Pura
Escobet Canal, Teresa
Sanmiquel Pera, Lluís
Bascompta Massanes, Marc

Stochastic model predictive control approaches applied to drinking water networks
http://hdl.handle.net/2117/108961
Stochastic model predictive control approaches applied to drinking water networks
Grosso Perez, Juan Manuel; Velarde, Pablo; OcampoMartínez, Carlos; Maestre Torreblanca, José María; Puig Cayuela, Vicenç
Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose different constraints for ensuring a reliable water supply in the most economic and safe ways. To cope with uncertainty in system disturbances due to the stochastic water demand/consumption and optimize operational costs, this paper proposes three stochastic model predictive control (MPC) approaches, namely, chanceconstrained MPC, treebased MPC, and multiplescenario MPC. A comparative assessment of these approaches is performed when they are applied to real case studies, specifically, a sector and an aggregate version of the Barcelona drinking water network in Spain.
Mon, 23 Oct 2017 10:03:21 GMT
http://hdl.handle.net/2117/108961
20171023T10:03:21Z
Grosso Perez, Juan Manuel
Velarde, Pablo
OcampoMartínez, Carlos
Maestre Torreblanca, José María
Puig Cayuela, Vicenç
Control of drinking water networks is an arduous task, given their size and the presence of uncertainty in water demand. It is necessary to impose different constraints for ensuring a reliable water supply in the most economic and safe ways. To cope with uncertainty in system disturbances due to the stochastic water demand/consumption and optimize operational costs, this paper proposes three stochastic model predictive control (MPC) approaches, namely, chanceconstrained MPC, treebased MPC, and multiplescenario MPC. A comparative assessment of these approaches is performed when they are applied to real case studies, specifically, a sector and an aggregate version of the Barcelona drinking water network in Spain.

Novel hybrid fuzzyPID control scheme for air supply in PEM fuelcellbased systems
http://hdl.handle.net/2117/108960
Novel hybrid fuzzyPID control scheme for air supply in PEM fuelcellbased systems
Baroud, Zakaria; Benmiloud, Mohammed; Benalia, Atallah; OcampoMartínez, Carlos
This paper proposes a novel hybrid fuzzyPID controller for air supply on Proton Exchange Membrane fuel cell (PEMFC) systems. The control objective is to adjust the oxygen excess ratio at a given setpoint in order to prevent oxygen starvation and damage of the fuelcell stack. The proposed control scheme consists of three parts: a fuzzy logic controller (FLC), a fuzzybased selftuned PID (FSTPID) controller and a fuzzy selector. Depending on the value of the error between the current value of oxygen excess ratio and its setpoint value, the fuzzy selector decides which controller should play the greatest effect on the control system. The performance of the proposed control strategy is analysed through simulations for different load variations and for parameter uncertainties. The results show that the novel hybrid fuzzyPID controller performs significantly better than the classical PID controller and the FLC in terms of several key performance indices such as the Integral Squared Error (ISE), the Integral Absolute Error (IAE) and the Integral Timeweighted Absolute Error (ITAE), as well as the overshoot, settling and rise time for the closedloop control system.
© <year>. This manuscript version is made available under the CCBYNCND 4.0 license http://creativecommons.org/licenses/byncnd/4.0/
Mon, 23 Oct 2017 09:51:44 GMT
http://hdl.handle.net/2117/108960
20171023T09:51:44Z
Baroud, Zakaria
Benmiloud, Mohammed
Benalia, Atallah
OcampoMartínez, Carlos
This paper proposes a novel hybrid fuzzyPID controller for air supply on Proton Exchange Membrane fuel cell (PEMFC) systems. The control objective is to adjust the oxygen excess ratio at a given setpoint in order to prevent oxygen starvation and damage of the fuelcell stack. The proposed control scheme consists of three parts: a fuzzy logic controller (FLC), a fuzzybased selftuned PID (FSTPID) controller and a fuzzy selector. Depending on the value of the error between the current value of oxygen excess ratio and its setpoint value, the fuzzy selector decides which controller should play the greatest effect on the control system. The performance of the proposed control strategy is analysed through simulations for different load variations and for parameter uncertainties. The results show that the novel hybrid fuzzyPID controller performs significantly better than the classical PID controller and the FLC in terms of several key performance indices such as the Integral Squared Error (ISE), the Integral Absolute Error (IAE) and the Integral Timeweighted Absolute Error (ITAE), as well as the overshoot, settling and rise time for the closedloop control system.