| This thesis presents the application of model reference adaptive control for vapour compression systems. The physical models of vapour compression systems are highly nonlinear because of fluid properties and thermodynamic relations. The model uncertainties rise as state variables deviate from equilibrium during the transient phase. Such uncertainties and perturbed dynamics degrade the performance of a fixed-gain control system. The adaptive approach improves a system's response under similar conditions and perturbations. A comparative evaluation shows that the proposed approach is superior to an existing Linear-Quadratic Gaussian control in dealing with perturbations as well as input constraints. Further, by treating the existing control as a reference model, the addition of the adaptive algorithm will improve the robustness of the vapour compression systems. |
