Abstract
This work details an IMC-based pole placement controller tuning procedure for a multi-loop SISO system in the presence of model uncertainty. For a given uncertainty level, selection of the IMC low-pass filter parameter is done using Kalman filter poles and open-loop poles as respective lower and upper limits. Tuning is facilitated using a convex tuning parameter, which depends on both the structured singular value μ as a quantitative performance measure and closed-loop behaviour like overshoots and manipulated variable move sizes as qualitative measures. The method is applied here to a distributed parameter system using model control, but can be generally applied for any multi-loop SISO system using a state estimator. Using simulation studies it is shown that the ambiguity encountered during selection of the IMC filter constant is significantly reduced.
