Robustness assessment of model-based control for the archimedes wave swing - Valério, Duarte (2019)
In this paper the robustness of three model-based control strategies—internal model control (IMC) with linear models, IMC with neural network models, and feedback linearisation control—for the Archimedes Wave Swing (AWS), a device designed to produce electricity from the energy of sea waves, is assessed by checking how their performance, optimised for a neutral tide with a standard atmospheric pressure, changes under high and low tides, and under atmospheric pressure variations. The original AWS controller and latching control are used as a term of comparison. Simulation results show that, as a rule, low tides and lower atmospheric pressures lead to higher power productions, while high tides and higher atmospheric pressures lead to lower power productions; but, in spite of model maladjustments, model-based control strategies are not at disadvantage when compared with latching control.