An ANOVA Based Analytical Dynamic Matrix Controller Tuning Procedure for FOPDT Models

Dynamic Matrix Control (DMC) is a widely used model predictive controller (MPC) in industrial plants. The successful implementation of DMC in practical applications requires a proper tuning of the controller. The available tuning procedures are mainly based on experience and empirical results. This paper develops an analytical tool for DMC tuning. It is based on the application of Analysis of Variance (ANOVA) and nonlinear regression analysis for First Order plus Dead Time (FOPDT) process models. It leads to a simple formula which involves the model parameters. The proposed method is validated via simulations as well as experimental results. A nonlinear pH neutralization model is used for the simulation studied. It is further implemented on a laboratory scale control level plant. A robustness analysis is performed based on the simulation results. Finally, comparison results are provided to show the effectiveness of the proposed methodology.