Smith predictor-based feedforward controller for measurable disturbances

This paper proposes a feedforward extension for the simplified filtered Smith predictor (SFSP) to deal with measurable disturbances. The proposed strategy uses a state-space formulation and can be applied in unified manner to stable, unstable, and integrating linear dead-time processes of any order. The main advantage with using the predictor approach in comparison with other control strategies is the ability to deal with processes with large dead time. The structure improves the disturbance rejection performance by feedforwarding the disturbance while maintaining the good robustness and noise attenuation properties of the SFSP. Simulation results show better performance indices compared with other strategies from the recent literature. In addition, the proposed strategy is applied to control the temperature in a newborn intensive care unit (NICU) to show its effectiveness in a real process.