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

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

Topological analysis of water distribution networks for optimal leak localization

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

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

Leak detection in water distribution networks based on water demand analysis

This paper deals with the leak detection problem in Water Distribution Networks (WDN). A leak detection method based on the water demand analysis of District Metered Areas (DMAs) is proposed. Historical leak-free data of water demand flow is used to extract minimum, and maximum values, and statistical distributions of differences (errors) between demand flow and predicted values at the different time hours of the day. The concept of sensor fusion is applied to reduce measurement uncertainties. For this, a virtual measurement is generated that considers each hour of the day a feature and, combined, develops a more accurate error analysis capable of detecting leaks and estimating the leak size magnitude. Furthermore, to increase the accuracy of the leak detection method, prediction errors are analyzed in a moving time window. Finally, the performance of the proposed leak detection method is assessed by using actual data of different real DMAs of the Barcelona WDN.Peer ReviewedPostprint (published version

Input-delay model predictive control of inland waterways considering the backwater effect

Inland waterways are large-scale systems, generally characterized by negligible bottom slopes and large time delays. These features pose challenging problems at the modeling and controller design stages. A control-oriented model is derived in this work, which allows to handle these issues in a suitable manner. A predictive control scheme is developed to ensure the coordination of the control actions and their delayed effects in the system. The proposed approach is tested on a case study to highlight its performance, and it is shown that it is possible to guarantee the navigability condition of the waterways as well as other operational goals. © 2018 IEEE.Peer ReviewedPostprint (author's final draft

Gray-Box model of inland navigation channel: application to the Cuinchy–Fontinettes reach

In a context of global change, inland navigation transport has gained interest with economic and environmental benefits. The development of this means of conveyance requires the improvement of its management rules to deal with the increase of navigation (schedules and frequency) and the potential impact of global change. To achieve this aim, it is first necessary to have a better knowledge about the dynamics of inland navigation networks and their interaction with the environment. Second, the potential effects of global change have to be anticipated. This article focuses on the modeling of inland navigation reaches. An inland navigation network is a large-scale distributed system composed of several interconnected reaches. These reaches are characterized by non-linearities, time delays, and generally no significant slope. To deal with these particularities, a gray-box model is proposed. It consists in determining the delays according to the physical characteristics of the system. The parameters of the model are identified with measured data. The gray-box model is used to reproduce the dynamics of the Cuinchy–Fontinettes reach located in the north of France.Postprint (author’s final draft

Sliding window assessment for sensor fault model-based diagnosis in inland waterways

The Cuinchy-Fontinettes reach belongs to the inland waterways in the north of France. It is equipped with limnimeters that measure water level data for the management of the water resources. These data can be corrupted by constant or intermittent faults. Hence, it is necessary to detect and localize these faults in order to guarantee efficient management actions. The proposed fault diagnosis method is based on the analysis of the parameters of a grey-box model. These parameters are obtained from available real data by using a sliding window, whose size is determined based on the level of excitation of input signals. Then, several scenarios involving constant and intermittent faults are proposed to discuss the performance of the proposed FDI approach as well as the effect of the sliding window size on the resultsPeer ReviewedPostprint (author's final draft