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Comparison of PID Controller with Model Predictive Controller for Milk Pasteurization Process Tesfaye Alamirew; V. Balaji; Nigus Gabbeye
Bulletin of Electrical Engineering and Informatics Vol 6, No 1: March 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v6i1.575

Abstract

Proportional–Integral–Derivative (PID) controllers are used in many of the Industries for various process control applications. PID controller yields a long settling time and overshoot which is not good for the process control applications. PID is not suitable for many of the complex process control applications. This research paper is about developing  a better type of controller, known as MPC (Model Predictive Control). The aim of the paper is to design MPC and PID for a pasteurization process. In this manuscript comparison of PID controller with MPC is made and the responses are presented. MPC is an advanced control strategy that uses the internal dynamic model of the process and a history of past control moves and a combination of many different technologies to predict the future plant output. The dynamics of the pasteurization process was estimated by using system identification from the experimental data. The quality of different model structures was checked using best fit with data validation, residual and stability analysis. Auto-regressive with exogenous input (ARX322) model was chosen as a model structure of the pasteurization process and fits about 80.37% with datavalidation. MPC and PID control strategies were designed using ARX322 model structure. The controller performance was compared based on settling time, percent of overshoot and stability analysis and the results are presented.
Comparison of PID Controller with Model Predictive Controller for Milk Pasteurization Process Tesfaye Alamirew; V. Balaji; Nigus Gabbeye
Bulletin of Electrical Engineering and Informatics Vol 6, No 1: March 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (650.155 KB) | DOI: 10.11591/eei.v6i1.575

Abstract

Proportional–Integral–Derivative (PID) controllers are used in many of the Industries for various process control applications. PID controller yields a long settling time and overshoot which is not good for the process control applications. PID is not suitable for many of the complex process control applications. This research paper is about developing  a better type of controller, known as MPC (Model Predictive Control). The aim of the paper is to design MPC and PID for a pasteurization process. In this manuscript comparison of PID controller with MPC is made and the responses are presented. MPC is an advanced control strategy that uses the internal dynamic model of the process and a history of past control moves and a combination of many different technologies to predict the future plant output. The dynamics of the pasteurization process was estimated by using system identification from the experimental data. The quality of different model structures was checked using best fit with data validation, residual and stability analysis. Auto-regressive with exogenous input (ARX322) model was chosen as a model structure of the pasteurization process and fits about 80.37% with datavalidation. MPC and PID control strategies were designed using ARX322 model structure. The controller performance was compared based on settling time, percent of overshoot and stability analysis and the results are presented.
Design of Model Predictive Controller for Pasteurization Process Tesfaye Alamirew; V. Balaji; Nigus Gabbeye
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 5, No 2: June 2017
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v5i2.279

Abstract

This research paper is about developing a better type of controller, known as MPC (Model Predictive Control) for pasteurization process plant. MPC is an advanced control strategy that uses the internal dynamic model of the process and a history of past control moves and a combination of many different technologies to predict the future plant output.. The dynamics of the pasteurization process was estimated by using system identification from the experimental data. The quality of model structures like ARX, ARMAX, BJ and CT model structures was checked based on  best fit with validation data, residual analysis and stability analysis. Auto-regressive with exogenous input (ARX322) model was chosen as a model structure of the pasteurization process dynamics and fits about 79.75% with validation data. Finally MPC control strategies were designed using ARX322 model structure.  
Comparison of PID Controller with Model Predictive Controller for Milk Pasteurization Process Tesfaye Alamirew; V. Balaji; Nigus Gabbeye
Bulletin of Electrical Engineering and Informatics Vol 6, No 1: March 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (650.155 KB) | DOI: 10.11591/eei.v6i1.575

Abstract

Proportional–Integral–Derivative (PID) controllers are used in many of the Industries for various process control applications. PID controller yields a long settling time and overshoot which is not good for the process control applications. PID is not suitable for many of the complex process control applications. This research paper is about developing  a better type of controller, known as MPC (Model Predictive Control). The aim of the paper is to design MPC and PID for a pasteurization process. In this manuscript comparison of PID controller with MPC is made and the responses are presented. MPC is an advanced control strategy that uses the internal dynamic model of the process and a history of past control moves and a combination of many different technologies to predict the future plant output. The dynamics of the pasteurization process was estimated by using system identification from the experimental data. The quality of different model structures was checked using best fit with data validation, residual and stability analysis. Auto-regressive with exogenous input (ARX322) model was chosen as a model structure of the pasteurization process and fits about 80.37% with datavalidation. MPC and PID control strategies were designed using ARX322 model structure. The controller performance was compared based on settling time, percent of overshoot and stability analysis and the results are presented.