… of parameter control, ie the dynamic and automated variation of values for parameters used
in … The method uses an evaluation of the recent performance of previously applied parameter …

… Thus, the control law only depends on the process parameter and only tuning parameter in
the EHAC method is the prediction horizon N . In EHAC, only the deviation at one moment in …

… through Linear Parameter Varying (LPV) embedding, and being this framework very
popular for control design, this paper investigates the available Model Predictive Control (MPC) …

… tuning guidelines for model predictive control, from theoretical and … dynamic matrix control
and generalized predictive control … parameters, the authors allow the user to set the prediction …

… The weight coefficients are key tuning parameters. By assigning appropriate values to these
parameters we can indicate the relative importance of the control goals. In general, larger R …

… prediction method, predictive parameter control outperforms state of the art parameter control
methods when the performance data adheres to the assumptions made by the prediction …

… In this paper a type of model based predictive control algorithm is used. The basic idea of …
control system by using a few candidate control sequences [17]. Then, using rule based control …

… there are parameter mismatches, MPC can still control the plant, but … parameter mismatch
have been proposed in literature [110], the most common solution being the use of a parameter …

… This paper presents a predictive-control-based DPC with an online parameter identification
technique to overcome model mismatches for an AFE. The proposed parameter tuning algo…

… MPC such as dynamic matrix control, generalized predictive control, and state-space-model …
parameters increased. The tunable parameters now include prediction horizons, control …