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In 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., Water Resources

Navigation canals are used for transport purposes. In order to allow safe navigation the water level should be kept in a certain range around the Normal Navigation Level (NNL). The water level is disturbed by known and unknown inputs, like tributaries, municipal water flows, rain, etc. Some of these inputs can be used to control the water level. If the geometry requires it, canal reaches are connected by locks. The operation of these locks sometimes can disturb the water level, if the difference between the upstream and downstream water level is large. The objective is to minimize the disturbances caused by these lock operations on the water level in order to maintain the NNL. In this work the global management of the canal reach is discussed and an option to maintain the NNL by active control is introduced. Some inputs to the system, such as other confluences or gates on the side of the locks, can be controlled automatically to react to the disturbances caused by the lock operations using model predictive control to maintain the desired water level.

Navigation canals are used for transport purposes. In order to allow safe navigation the water level should be kept in a certain range around the Normal Navigation Level (NNL). The water level is disturbed by known and unknown inputs, like tributaries, municipal water flows, rain, etc. Some of these inputs can be used to control the water level. If the geometry requires it, canal reaches are connected by locks. The operation of these locks sometimes can disturb the water level, if the difference between the upstream and downstream water level is large. The objective is to minimize the disturbances caused by these lock operations on the water level in order to maintain the NNL. In this work the global management of the canal reach is discussed and an option to maintain the NNL by active control is introduced. Some inputs to the system, such as other confluences or gates on the side of the locks, can be controlled automatically to react to the disturbances caused by the lock operations using model predictive control to maintain the desired water level., Postprint (published version)

Automated control of water systems (irrigation canals, navigation canals, rivers etc.) relies on the measured data. The control action is calculated, in case of feedback controller, directly from the on-line measured data. If the measured data is corrupted, the calculated control action will have a different effect than it is desired. Therefore, it is crucial that the feedback controller receives good quality measurement data. On-line fault detection techniques can be applied in order to detect the faulty data and correct it. After the detection and correction of the sensor data, the controller should be able to still maintain the set point of the system. In this paper this principle using the sensor fault masking is applied to model predictive control of open channels. A case study of a reach of the northwest of the inland navigation network of France is presented. Model predictive control and water level sensor masking is applied., Peer Reviewed, Postprint (published version)

In recent years, inland navigation networks benefit from the innovation of the instrumentation and SCADA systems. These data acquisition and control systems le d 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., Peer Reviewed, Postprint (published version)

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)

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., Peer Reviewed, Postprint (author’s final draft)

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 bene¿t 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 Reviewed, Postprint (author's final draft)

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.

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.

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 realized, Peer Reviewed, Postprint (author’s final draft)

Inland navigation networks are mainly used for transport with economic and environmental benefits. In a climate change context which leads to the scarcity of the water resource, the control of navigation levels and the supervision of these networks become crucial. Thus, this paper is focused on the sensors Fault Detection and Isolation of inland navigation reaches. A modeling method based on the identification technique is proposed. Then, based on residuals, the dynamic classification algorithm AUDyC leads to the detection and diagnosis of sensors faults. Setting errors and slow drifts are considered. The proposed methods are applied on the Cuinchy- Fontinettes reach benchmark., Peer Reviewed, Postprint (author’s final draft)

Inland navigation networks offer an alternative to land transport with economic and environmental benefits, and direct access to urban and industrial centers. Promoting the navigation transport requires the modernization of the network management, in particular the control of navigation levels and the improvement of the network safety. To reach these aims, modeling methods of the inland navigation networks have to be proposed. These networks are large scale distributed systems characterized by non-Iinearities, time-delays and generally no significant slope. A modeling method of a navigation channel based on identification method is proposed in this paper. It is applied on the Cuinchy-Fontinettes reach located in the north of France., Peer Reviewed, Postprint (published version)

This paper focuses on the Normal Navigation Level (NNL) control of a hydraulic channel that is located in the northwest of France and belongs to the Europe Inland Navigation Network. This system is a large scale system with several inputs and outputs that nowadays is operated manually and with local controllers that try to maintain the level of the channel as close as possible to the NNL and fulfils the seaworthiness requirements. For recent years, the channel has been equipped with electronic sensors in order to have better knowledge of its behaviour, provide online the state to the lockkeepers and improve its management. In this work, an automatic control based on a Model Predictive Controller (MPC) is proposed. The MPC controller is based on a model of the system and, with the available data, provides automatically the suitable control inputs (flows) in order to maintain the level in all the points of the channel despite the locks operation that produces wave phenomena and other unknown inputs along the channel. A numerical simulator of the system based on the Saint-Venant Equations and calibrated with real data has been developed in order to verify the effectiveness of the proposed automatic controller., Peer Reviewed, Postprint (author’s final draft)

Peer Reviewed, Postprint (published version)

Automated control of water systems (irrigation canals, navigation canals, rivers etc.) relies on the measured data. The control action is calculated, in case of feedback controller, directly from the on-line measured data. If the measured data is corrupted, the calculated control action will have a different effect than it is desired. Therefore, it is crucial that the feedback controller receives good quality measurement data. On-line fault detection techniques can be applied in order to detect the faulty data and correct it. After the detection and correction of the sensor data, the controller should be able to still maintain the set point of the system. In this paper this principle using the sensor fault masking is applied to model predictive control of open channels. A case study of a reach of the northwest of the inland navigation network of France is presented. Model predictive control and water level sensor masking is applied., Peer Reviewed, Postprint (published version)