A predictor for dead-time systems based on the Kalman Filter for improved disturbance rejection and robustness. (September 2021) - Lima, Daniel Martins; Lima, Bruno Martins; Normey-Rico, Julio Elias
Abstract: Dead-time processes are common in industry and represent a challenge for feedback control. The use of predictor structures with the controllers can attenuate this. A predictor is proposed here based on the Kalman filter, the Kalman Predictor (KP), that has only one tuning parameter for SISO systems and can be used with non-minimum phase, open-loop unstable and integrative systems of any order, and is also capable of estimating many types of disturbances. It is shown that the KP implicitly defines a Filtered Smith Predictor (FSP), hence, all tools used to analyze the closed-loop properties of the FSP can be used, including robustness and disturbance rejection. Tuning guidelines are provided and simulation examples with comparisons with other predictor structures are used to illustrate the advantages of the proposed KF. Highlights: A predictor based on the Kalman Filter is proposed, the Kalman Predictor. It implicitly defines a Filtered Smith Predictor and has the same properties. The predictor has a single tuning parameter, independent of system order or dynamics. Can cope with systems of any order or dynamics (non-minimum phase, unstable, etc.). Can be designed to properly estimate different disturbance types (step, sinusoid, etc.).