Robust tuning of dynamic matrix controllers for first order plus dead time models

Dynamic Matrix Control is a widely used Model Predictive Controller in industrial processes. The successful implementation of Dynamic Matrix Control in practical applications requires appropriate tuning of the controller parameters. Three different cases are considered. In the first case, a tuning formula is developed that ensures the nominal closed loop desired performance. However, this formula may fail in the presence of plant uncertainty. Therefore a lower bound for the tuning parameter is derived to secure the robust stability of the uncertain first order plus dead time plant. Finally, a tuning boundary is derived which gives the lower and upper permissible bounds for the tuning parameter that guarantee the robust performance of the uncertain first order plus dead time plant. The tuning procedure is based on the application of Analysis of Variance, curve fitting and nonlinear regression analysis. The derived results are validated via simulation studies and some experimental results.