DISTURBANCE REJECTION IN MODEL FREE ADAPTIVE CONTROL USING FEEDBACK

摘要

Model Free Adaptive Control guarantees good control performance without having any substantial information about the plant to be controlled. The particular type of model free controller discussed in the paper is based on the inverse plant model. The controller effectively maintains the temperature by adjusting the water flow rate through the cooling coil in an experimental test rig. The controller is shown to be robust and the particular structure complements the learning scheme. The fuzzy learning scheme, which is based on the feedback error learning strategy, determines an inverse model of the plant online. The simulation as well as the results from the experimental test rig clearly indicates the effectiveness of the feedback control structure as compared to the feedforward control scheme in rejecting unmeasured disturbances.