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Anamika Bhatia Jain
Graphic Era University
Computer Science & IT Electrical & Electronics Engineering Engineering

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Model Predictive Control System Analysis for Sugarcane Crushing Mill Process Sunori, Sandeep Kumar; Kumar Juneja, Pradeep; Bhatia Jain, Anamika
Bulletin of Electrical Engineering and Informatics Vol 4, No 3: September 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v4i3.459

Abstract

MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In this paper the performance of an MPC controller on a single stage of milling train of sugar mill is analyzed. A linear model of the plant is taken with flap position and turbine speed set point as manipulated variables and mill torque and buffer chute height as controlled variables. The set point tracking responses are compared for constrained and unconstrained cases. The effect of presence of unmeasured disturbance also is investigated.
Model Predictive Control System Analysis for Sugarcane Crushing Mill Process Sunori, Sandeep Kumar; Kumar Juneja, Pradeep; Bhatia Jain, Anamika
Bulletin of Electrical Engineering and Informatics Vol 4, No 3: September 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v4i3.459

Abstract

MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In this paper the performance of an MPC controller on a single stage of milling train of sugar mill is analyzed. A linear model of the plant is taken with flap position and turbine speed set point as manipulated variables and mill torque and buffer chute height as controlled variables. The set point tracking responses are compared for constrained and unconstrained cases. The effect of presence of unmeasured disturbance also is investigated.
Co-Authors Pradeep Kumar Juneja Sandeep Kumar Sunori