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Model Predictive Control (MPC) is a well-established advanced process control technology. There are many successful implementations of different predictive strategies in process industry. There may be found various modifications of the MPC, however, one aspect remains fixed. MPC performance index is in quadratic form. Nonetheless, statistical analysis frequently points out that the quadratic regression formulation has some drawbacks. It is sensitive against the outliers. This work analyzes alternative and robust formulations of the MPC embedded performance index. It is shown that the quadratic formulation is not an optimal one, while the linear &#x2113;<sub>1</sub> weight improves control. Classical &#x2113;<sub>2</sub> norm together with robust Cauchy and Dynamic Covariance Scaling gives worse results.

Impact of MPC Embedded Performance Index on Control Quality