Model predictive control and moving horizon estimation for water level regulation in inland waterways.

• A delayed formulation using additional matrices is derived to model inland waterways. • The static behavior characterization leads to a delayed descriptor model formulation. • The LQR and the KF formulation needs to be extended to deal with such systems. • By contrast, MPC and MHE can be easily adapted for this formulation • This approach can be applied to any system characterized by a static behavior. This work regards the design of optimization techniques for the purposes of state estimation and control in the framework of inland waterways, often characterized by negligible bottom slopes and large time delays. The derived control-oriented model allows these issues to be handled in a suitable manner. Then, the analogous moving horizon estimation and model predictive control techniques are applied in a centralized manner to estimate the unmeasurable states and fulfill the operational goals, respectively. Finally, the performance of the methodology is tested in simulation by means of a realistic case study based on part of the inland waterways in the north of France. The results show that the proposed methodology is able to guarantee the navigability condition, as well as the other operational goals. [ABSTRACT FROM AUTHOR]