(184c) A Modified IMC Strategy for Unstable and Integrating Systems

Internal Model Control (IMC) is a model based control approach which has several advantages owing to its simple and transparent design and its applicability in as a PID controller structure through an appropriate filter. In this study, a modified IMC strategy for unstable systems has been proposed. The feedback IMC structure consists of three major components: a stabilizing controller, a compensator and the other having a PI/PID structure. The IMC controller is factorized into two parts having minimum phase and non-minimum phase components. A structural change is done, which forms an inner loop involving updated model with non-minimum phase component of IMC, which upon simplification yields a PI/PID structure. A pure gain controller, which can be adjusted suitably, is added in the loop to stabilize the system. The proposed method is applied on different transfer function models and simulation study has been carried out to compare the results with standard IMC-PID settings from Bequette (2003). Study has been conducted to check the robustness of the system under model uncertainty. To evaluate the efficacy of this method, a study has been carried out using this approach on an inverted pendulum model. This new methodology has been extended to integrating systems also. Simulation study for a time delayed integrating system is done and the results are compared with methods stated by Shamsuzzoha and Lee (2008) and Zhang et al. (1999). The proposed control law has also been applied to a four tank interacting liquid storage system showing integrating behaviour (Reddy and Saha, 2012) and performance has been compared with IMC-PID settings (Bequette, 2003). All the simulation studies have shown the usefulness of the modified IMC approach in process applications.

References

1. Shamsuzzoha M. and Monnyong Lee (2008). “Analytical design of enhanced PID filter controller for integrating and first order unstable processes with time delay”, Chemical Engineering Science, 63(10), pp. 2717-2731
2. Bequette B. Wayne (2003). Process Control: Modeling, Design and Simulation, Prentice-Hall International Series in the Physical and Chemical Engineering Sciences.
3. Reddy B. Rajasekhara and Prabirkumar Saha (2012). “Real time model predictive control of a four tank interacting storage system”, 11^th International Symposium on Process Systems Engineering, volume 31 of Computer Aided Chemical Engineering, pages 335-339. Elsevier.
4. Zhang W., X. Xu and Y. Sun (1999). “Quantitative performance design for integrating processes with time delay”, Automatica, 35(4), pp. 719-723.