Smith Predictor Based Parallel Cascade Control Strategy for Unstable Processes with Application to a Continuous Bioreactor

Abstract

Abstract In this paper, Smith predictor based parallel cascade control strategy is proposed for enhanced control of continuous bioreactor. The scheme consists of secondary loop and primary loop. The secondary loop controller is designed based on the direct synthesis method. Then, the overall primary loop process model is identified using least square method. A delay compensation strategy is incorporated in the primary loop and the corresponding primary loop delay compensated controller is designed based on the identified primary loop model. For comparison, a simple parallel cascade control and a simple feedback control is also applied to the continuous bioreactor. From the simulation studies, it is observed that delay compensated control strategy provides enhanced closed loop performances compared to that of the simple parallel cascade control and simple feedback control. To analyze the performance in the presence of uncertainties, robustness analysis has been carried out based on sensitivity and complementary sensitivity functions.