106 research outputs found

    Adaptive and predictive control architecture of inland navigation networks in a global change context: application to the Cuinchy-Fontinettes reach

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    In this paper, an adaptive and predictive control architecture is proposed to improve the management of inland navigation networks in a global change context. This architecture aims at ensuring the seaworthiness conditions of inland navigation networks, and to improve the efficiency of the water resource management. It is based on supervision and prognosis modules which allow the estimation of the current state of the network, and the forecasting of the extreme event occurrence. According to these indicators and to the management constraints and objectives, control strategies of the inland navigation networks will be adapted to limit the impacts of the extreme events. To achieve this aim, three challenges are considered and discussed in this paper. The first one consists in proposing an accurate modeling approach of navigation reaches which are characterized by large scale, nonlinearities, time delays, unknown inputs and outputs, etc. The second one is to increase the knowledge about potentiality of extreme events, consequences of the climate change. The prediction of these events is rather complex due to their rarity, the spacio-temporal scale of the networks, etc. Finally, the third one is the pooling of the two first contributions, i.e. the model of the system and the knowledge about extreme events. Thus, the resilience of the system and the adaptation of the management strategies could be realizedPeer ReviewedPostprint (author’s final draft

    Study of Global Change Impacts on the Inland Navigation Management: Application on the Nord-Pas de Calais Network

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    AbstractIn a global change context, governments in Europe want to promote alternative transports as inland navigation or railway instead of road transport. As example, in north of France, a shift of 20% from road transport to these alternative transport solutions is expected by 2050. Reaching this goal requires not only the delivery of new infrastructures and equipment, but also the design of efficient management strategies. By focusing on waterborne transport, it is thus necessary to improve the management of the inland navigation networks particularly the water resource. Indeed, the waterborne transport accommodation is strongly linked to the available water resource. This will be a challenging point in a global change context.The paper deals with the global change impacts on inland navigation networks. It aims at proposing new contributions as compared to past and current results of European projects on climate change and inland navigation. It appeared that the multi-scale modeling approach for inland navigation networks that was proposed during the last TRA Conference in Paris in 2014 is useful to determine the resilience of these networks and their ability to guarantee the navigation conditions during drought and flood periods. The proposed tools are developed to consider two space and time scales. The first approach is used to determine the water quantity that is necessary to accommodate the navigation during half a day, and the second allows the efficient control of the gates to keep the water level of each navigation reach close to its setpoint by rejecting disturbances and compensating the waves due to the lock operations. One example based on the real inland navigation network of the north of France is used to highlight the contributions of the multi-scale modeling approach

    Decentralized fault-tolerant control of inland navigation networks: a challenge

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    Inland waterways are large-scale 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 fault-tolerant 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.Peer ReviewedPostprint (published version

    A communication-based distributed model predictive control approach for large-scale systems

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    This work presents a distributed model predictive control strategy as an alternative to conventional centralized approaches, which often suffer from implementation issues when applied to large-scale systems. The overall system is partitioned into minimally coupled subsystems based on its structural properties. Then, the coordination among the subproblems is achieved by means of a communication protocol, which allows each local controller to broadcast its solution to the rest of controllers with a coupled variable. The proposed approach is tested on the quadruple-tank process, and its effectiveness is proved by comparing the obtained results to those documented in an existing benchmark.Peer ReviewedPostprint (author's final draft

    Sensor fault diagnosis of inland navigation system using physical model and pattern recognition approach

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    Trabajo presentado al 19th IFAC World Congress celebrado del 24 al 29 de agosto de 2014 en Cape Town (Sudafrica).In recent years, inland navigation networks benefit from the innovation of the instrumentation and SCADA systems. These data acquisition and control systems lead to a reactive asset-management of inland navigation networks. However, sensors and actuators are subject to faults due to the strong effects of the environment, aging, etc. In this paper, a sensor Fault Detection and Isolation (FDI) approach is proposed using an Integrator-Delay-Zero (IDZ) model, interval observers and the dynamic classification algorithm AUDyC. The combined use of these approaches allows the improvement of the sensor fault diagnosis. The proposed approach is introduced through the case study of the Cuinchy-Fontinettes reach in the north of France.This work is a contribution to the GEPET’Eau project which is granted by the French ministery MEDDE - GICC, the French institution ORNERC and the DGITMPeer Reviewe

    Model-based sensor supervision inland navigation networks: Cuinchy-Fontinettes case study

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    In recent years, inland navigation networks benefit from the innovation of the instrumentation and SCADA systems. These data acquisition and control systems lead to the improvement of the manage- ment of these networks. Moreover, they allow the implementation of more accurate automatic control to guarantee the navigation requirements. However, sensors and actuators are subject to faults due to the strong effects of the environment, aging, etc. Thus, before implementing automatic control strate- gies that rely on the fault-free mode, it is necessary to design a fault diagnosis scheme. This fault diagnosis scheme has to detect and isolate possible faults in the system to guarantee fault-free data and the efficiency of the automatic control algorithms. Moreover, the proposed supervision scheme could predict future incipient faults that are necessary to perform predictive maintenance of the equipment. In this paper, a general architecture of sensor fault detection and isolation using model-based approaches will be proposed for inland navigation networks. The proposed approach will be particularized for the Cuinchy-Fontinettes reach located in the north of France. The preliminary results show the effectiveness of the proposed fault diagnosis methodologies using a realistic simulator and fault scenarios.In recent years, inland navigation networks beneÂżt from the innovation of the instrumentation and SCADA systems. These data acquisition and control systems lead to the improvement of the management of these networks. Moreover, they allow the implementation of more accurate automatic control to guarantee the navigation requirements. However, sensors and actuators are subject to faults due to the strong effects of the environment, aging, etc. Thus, before implementing automatic control strategies that rely on the fault-free mode, it is necessary to design a fault diagnosis scheme. This fault diagnosis scheme has to detect and isolate possible faults in the system to guarantee fault-free data and the efficiency of the automatic control algorithms. Moreover, the proposed supervision scheme could predict future incipient faults that are necessary to perform predictive maintenance of the equipment. In this paper, a general architecture of sensor fault detection and isolation using model-based approaches will be proposed for inland navigation networks. The proposed approach will be particularized for the Cuinchy-Fontinettes reach located in the north of France. The preliminary results show the effectiveness of the proposed fault diagnosis methodologies using a realistic simulator and fault scenarios.Peer ReviewedPostprint (author's final draft

    Model-based sensor supervision in inland navigation networks: Cuinchy-Fontinettes case study

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    Trabajo presentado a la 6th International Conference on Maritime Transport (MT'14) celebrada en Barcelona del 25 al 27 de junio de 2014.In recent years, inland navigation networks benefit from the innovation of the instrumentation and SCADA systems. These data acquisition and control systems lead to the improvement of the management of these networks. Moreover, they allow the implementation of more accurate automatic control to guarantee the navigation requirements. However, sensors and actuators are subject to faults due to the strong effects of the environment, aging, etc. Thus, before implementing automatic control strategies that rely on the fault-free mode it is necessary to design a fault diagnosis scheme. This fault diagnosis scheme has to detect and isolate possible faults in the system to guarantee fault-free data and the efficiency of the automatic control algorithms. Moreover, the proposed supervision scheme could predict future incipient faults that are necessary to perform predictive maintenance of the equipment. In this paper, a general architecture of sensor fault detection and isolation using model-based approaches will be proposed for inland navigation networks. It will be particularized for the Cuinchy-Fontinettes reach located in the north of France in order to show the effectiveness of the proposed fault diagnosis scheme. The preliminary results show the effectiveness of the proposed fault diagnosis methodologies using a realistic simulator and fault scenarios.This work has been partially funded by grants CICYT SHERECS DPI-2011-26243 of Spanish Ministry of Education and by GEPET’Eau project which is granted by the French ministery MEDDE-GICC, the French institution ORNERC and the DGITM.Peer Reviewe

    Data-driven leak localization in WDN using pressure sensor and hydraulic information

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    Maintaining a good quality of service under a wide range of operational management is challenging for water utilities. One of the significant challenges is the location of water leaks in the large-scale water distribution networks (WDN) due to limited data information throughout the system, generally having only flow sensors at the system's entrance and some pressure sensors in some selected nodes. In addition, most systems do not have a network hydraulic model. Therefore, when using the hydraulic model, the presence of model errors, such as nodal demand uncertainty and measurement noise, can interfere with the performance of the leak location method. This work presents a fully data-driven technique to reduce the area of the leak localization in the WDN, using Graph theory to represent the network. To do so, we have developed distance clustering with pre-defined centroids that are the sensor pressure information and some selected nodes. Furthermore, extra pressure information of leak events in the selected centroids is studied to develop a correlation between the pressure measurement and the event. Finally, the approach is evaluated in real-world water systems and discusses graphical results and key performance indicators.Peer ReviewedPostprint (published version

    Topological analysis of water distribution networks for optimal leak localization

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    This paper introduces two methodologies to provide an optimum sensor deployment layout, one based on a model-based approach and the other entirely data-driven. The first method is formulated as an integer optimization problem, an optimization criterion consisting of minimizing the average topological distance. The second method is a new methodology to provide an optimum sensor placement regarding how many sensors to install without using hydraulic information but just exploiting the knowledge of the topology of the Water Distribution Networks. The method uses the Girvan-Newman clustering algorithm to ensure complete coverage of the network and the study of the installation of pressure sensors in the central nodes of each group, selected according to different metrics of topological centrality. The approach is illustrated in the Modena network. © 2023 Institute of Physics Publishing. All rights reserved.Postprint (published version

    Robust data-driven leak localization in water distribution networks using pressure measurements and topological information

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    This article presents a new data-driven method for locating leaks in water distribution networks (WDNs). It is triggered after a leak has been detected in the WDN. The proposed approach is based on the use of inlet pressure and flow measurements, other pressure measurements available at some selected inner nodes of the WDN, and the topological information of the network. A reduced-order model structure is used to calculate non-leak pressure estimations at sensed inner nodes. Residuals are generated using the comparison between these estimations and leak pressure measurements. In a leak scenario, it is possible to determine the relative incidence of a leak in a node by using the network topology and what it means to correlate the probable leaking nodes with the available residual information. Topological information and residual information can be integrated into a likelihood index used to determine the most probable leak node in the WDN at a given instant k or, through applying the Bayes’ rule, in a time horizon. The likelihood index is based on a new incidence factor that considers the most probable path of water from reservoirs to pressure sensors and potential leak nodes. In addition, a pressure sensor validation method based on pressure residuals that allows the detection of sensor faults is proposed.This work has been partially funded by SMART Project (ref.num. EFA153/16 Interreg Cooperation Program POCTEFA 2014-2020), L-BEST Project (PID2020-115905RB-C21) funded by MCIN/ AEI /10.13039/501100011033 and AGAUR ACCIO RIS3CAT UTILITIES 4.0–P1 ACTIV 4.0. ref.COMRDI-16-1-0054-03.Peer ReviewedPostprint (published version
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