… Abstract: Model predictive control (MPC) relevant identification (MRI) … identification errors
from multistep ahead predictions. The multiple MISO (multiple input single output) identification …

… of the origins of model predictive control (MPC) … out new needs in related areas like system
identification, state estimation, monitoring and diagnostics, etc. We show that many important …

… a detection algorithm that is model predictive control relevant and has a … in model validation
for model predictive control systems. New residuals that are model predictive control relevant …

… of multi-input multi-output (MIMO) control systems and large scale model predictive control
(… The size and complexity of MPC systems means that identifying and diagnosing problems …

… to use model predictive control as a systematic way to go directly from high-level specifications
to a control … and is based on a model obtained through system identification. Experimental …

… models for model predictive control. In particular because, in order to compute the cost function
to be minimized, the output … a new structure for system identification of models for MPC is …

… standard multi-step ahead method. As a case study, we show a practical example, an
identification and modeling … , that the introduced multi-step ahead identification method has a …

An important difference between Model Predictive control (MPC) and PID-kind designmethods
is the explicit use of a model. This aspect is both the advantage and the disadvantage of …

… estimation algorithms are used to identify linear and neural state-space and input–output …
surrogate models to be used as predictors in Model Predictive Control (MPC) controllers to …

… , “Model predictive control relevant identification using partial least squares for building
modeling,” in Australian Control … Prívara, “Experimental analysis of model predictive control for an …