Model-based control and diagnosis of inland navigation networks
- Autores: Pablo Segovia Castillo
- Directores de la Tesis: Eric Duviella (dir. tes.), Vicenç Puig (dir. tes.)
- Lectura: En la Universitat Politècnica de Catalunya (UPC) ( España ) en 2019
- Idioma: español
- Tribunal Calificador de la Tesis: Rudy Rafaël Negenborn (presid.), José María Maestre Torreblanca (secret.), Laurent Lefèvre (voc.)
- Programa de doctorado: Programa de Doctorado en Automática, Robótica y Visión por la Universidad Politécnica de Catalunya
- Materias:
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- Resumen
This thesis regards the problem of optimal management of water resources in inland navigation networks from a control theory perspective. In particular, the main objective to be attained consists in guaranteeing the navigability condition of the network, i.e., ensuring that the water levels are such that vessels can travel safely. More specifically, the water levels must be kept within an interval around the setpoint. Other common objectives include minimizing the operational cost and ensuring a long lifespan of the equipment. However, inland navigation networks are large-scale systems characterized by a number of features that complicate their management, namely complex dynamics, large time delays and negligible bottom slopes.
In order to achieve the optimal management, the efficient control of the hydraulic structures, e.g., gates, weirs and locks, must be ensured. To this end, a control-oriented modeling approach is derived based on an existing simplified model obtained from the Saint-Venant equations. This representation reduces the complexity of the original model, provides flexibility and allows to coordinate current and delayed information in a systematic manner. However, the resulting model formulation belongs to the class of delayed descriptor systems, for which standard control and state estimation tools would need to be extended. Instead, model predictive control and moving horizon estimation can be easily adapted for this formulation, as well as being able to deal with physical and operational constraints in a natural manner.
Due to the large dimensionality of inland navigation networks, a centralized implementation is often neither possible nor desirable. In this regard, non-centralized approaches are considered, decomposing the overall system in subsystems and distributing the computational burden among the local agents, each of them in charge of meeting the local objectives. Given the fact that inland navigation networks are strongly coupled systems, a distributed approach is followed, featuring a communication protocol among local agents.
Despite the optimality of the computed solutions, state estimation will only be effective provided that the sensors acquire reliable data. Likewise, the control actions will only be applied correctly if the actuators are not impacted by faults. Indeed, any error can lead to an inefficient management of the system. Therefore, the last part of the thesis is concerned with the design of supervisory strategies that allow to detect and isolate faults in inland navigation networks.
All the presented modeling, centralized and distributed control and state estimation and fault diagnosis approaches are applied to a realistic case study based on the inland navigation network in the north of France to validate their effectiveness.
