This paper describes the synthesis of model-based predictive controllers for multivariable digital feedback systems in which the plant output signals are measured at a faster rate than the controls are applied. In contrast with the recent literature devoted to multirate sampled-data system theory, where state-variable system representations are used exclusively, a polynomial modelling approach that exploits the frequency and switch decomposition techniques established in the 1950s is adopted. It is demonstrated that the principal advantage of fast output signal-sampled predictive control algorithms lies in their potential to suppress process and, particularly, measurement noise disturbances.
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