This work proposes a new and simple design for the filtered Smith predictor (FSP), which belongs to a class of dead-time compensators (DTCs) and allows the handling of stable, unstable, and integrative processes. For this purpose, first, to use lower-order controller and filters, it is shown that it is not necessary to use the integral action in the primary controller, which is used to tune the set-point response; then, the FSP filters are designed to obtain the desired disturbance rejection, robustness, and noise attenuation. Using this procedure, it is possible to obtain a better compromise between performance and complexity than other solutions in the literature. Two simulation case studies are used to compare the obtained solution with some recently published results. A practical experiment involving a neonatal intensive care unit is also presented to illustrate the usefulness of the proposed DTC.

This paper proposes a robust multivariable predictive control algorithm that improves the robustness of closed loop systems, even when they have multiple time delays between the inputs and outputs. The desired robustness is achieved by including an appropriate filter on the disturbances model. The proposed algorithm is applied to the control of humidity and temperature of a neonatal incubator. Simulation and experimental results show the advantages of the proposed algorithm compared to others proposed in the literature.

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