Smith predictor based parallel cascade control strategy for unstable and integrating processes with large time delay. (April 2017) - Lloyds Raja, G.; Ali, Ahmad
Highlights: Smith predictor based parallel cascade control structure (PCCS) is proposed for a class of unstable and integrating process models. Does not require a hit and trial approach for selecting the primary and secondary closed-loop time constants ( λ 1 and λ 2 ). Yields improved and robust closed-loop performance compared to the recently reported parallel cascade control strategies. Abstract: This manuscript presents a modified parallel cascade control structure (PCCS) with Smith predictor for open loop unstable and integrating process models with large time delay. The proposed PCCS consists of a secondary disturbance rejection controller, a primary stabilizing controller and a primary setpoint tracking controller. Parameters of the setpoint tracking controller are obtained by equating the first and second derivatives of desired and actual closed-loop transfer functions at s = 0 whereas the secondary disturbance rejection controller is designed using internal model control approach. Routh–Hurwitz stability criterion is used to design the stabilizing controller of the primary loop. An analytical expression for computing the primary closed-loop time constant in terms of known plant model parameters is obtained. Moreover, a suitable value is recommended for the secondary closed-loop time constant based on extensive simulation studies. This is an advantage of the present work over the contemporary Smith predictor based parallel cascade control schemes where the authors provide suitable range of values for the closed-loop time constants. Simulation results illustrate that the proposed method yields significant improvement in closed-loop performance compared to the recently reported tuning strategies for nominal and perturbed process models.