This paper introduces a robust methodology for autotuning design parameters in the EPSAC (Extended Prediction Self-Adaptive Control) approach to MPC (Model based Predictive Control). The method requires from the user solely a well-chosen sampling period of the process and, in case of process with time delay, the amount of delayed samples. The main design parameter, the prediction horizon, is related to the open loop dynamics of the system and set to a relatively large value for a robust control performance. Process model is obtained apriori from step response in presence of 20% noise and later updated during closed loop simulations. The results indicate in both simulation and experimental study that the methodology is suitable for some clas...
Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process mo...
A two-layer approach for the auto-tuning of model predictive control (MPC) is proposed. The bottom l...
A two-layer approach for the auto-tuning of model predictive control (MPC) is proposed. The bottom l...
This paper introduces a robust methodology for autotuning design parameters in the EPSAC (Extended P...
Material or fluid transportation is a commonly encountered phenomenon in industrial applications, ge...
Material or fluid transportation is a commonly encountered phenomenon in industrial applications, ge...
Material or fluid transportation is a commonly encountered phenomenon in industrial applications, ge...
This paper proposes a practical tuning of closed loops with model based predictive control. The data...
Model predictive control (MPC) schemes employ dynamic models of a process within a receding horizon ...
This paper proposes a practical tuning of closed loops with model based predictive control. The data...
The recently introduced self-tuning Generalized Predictive Control (GPC) algorithm based on long ran...
The recently introduced self-tuning Generalized Predictive Control (GPC) algorithm based on long ran...
This paper proposes a practical tuning of closed loops with model based predictive control. The data...
Model Predictive Controller (MPC) technology has been researched and developed to meet varied demand...
Current generation of industrial MPC technology has two main disadvantages: 1) it is very costly to ...
Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process mo...
A two-layer approach for the auto-tuning of model predictive control (MPC) is proposed. The bottom l...
A two-layer approach for the auto-tuning of model predictive control (MPC) is proposed. The bottom l...
This paper introduces a robust methodology for autotuning design parameters in the EPSAC (Extended P...
Material or fluid transportation is a commonly encountered phenomenon in industrial applications, ge...
Material or fluid transportation is a commonly encountered phenomenon in industrial applications, ge...
Material or fluid transportation is a commonly encountered phenomenon in industrial applications, ge...
This paper proposes a practical tuning of closed loops with model based predictive control. The data...
Model predictive control (MPC) schemes employ dynamic models of a process within a receding horizon ...
This paper proposes a practical tuning of closed loops with model based predictive control. The data...
The recently introduced self-tuning Generalized Predictive Control (GPC) algorithm based on long ran...
The recently introduced self-tuning Generalized Predictive Control (GPC) algorithm based on long ran...
This paper proposes a practical tuning of closed loops with model based predictive control. The data...
Model Predictive Controller (MPC) technology has been researched and developed to meet varied demand...
Current generation of industrial MPC technology has two main disadvantages: 1) it is very costly to ...
Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process mo...
A two-layer approach for the auto-tuning of model predictive control (MPC) is proposed. The bottom l...
A two-layer approach for the auto-tuning of model predictive control (MPC) is proposed. The bottom l...