Control of pH neutralization system using nonlinear model predictive control with I-controller
In the process industry controlling the pH is considered to be one of the toughest tasks among the most commonly controlled variables. This is due to the nonlinear behavior of the pH and the time dependence of the nonlinearity, requiring an advanced controller. In this paper a multi-model nonlinear...
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my.upm.eprints.398312015-08-19T09:13:51Z http://psasir.upm.edu.my/id/eprint/39831/ Control of pH neutralization system using nonlinear model predictive control with I-controller Hermansson, A. W. Syafiie, Syafiie In the process industry controlling the pH is considered to be one of the toughest tasks among the most commonly controlled variables. This is due to the nonlinear behavior of the pH and the time dependence of the nonlinearity, requiring an advanced controller. In this paper a multi-model nonlinear model predictive control (MMNMPC) scheme is applied to describe and handle the nonlinearities, were the multi-model description gives a piecewise linear description enabling a simple and swift computation of control moves. MPC implementation requires the knowledge, through measurement or by estimation, of the states of the neutralization system, both creating various problems. Here problem is addressed by including integral action in the controller to compensate for the unmeasured states. The MMNMPC combined with integral action is tested by simulation of a pH system in Matlab and the control structures were applied in Matlab/YALMIP showing good control performance. IEEE (IEEE Xplore) 2014 Conference or Workshop Item NonPeerReviewed Hermansson, A. W. and Syafiie, Syafiie (2014) Control of pH neutralization system using nonlinear model predictive control with I-controller. In: 2014 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 9-12 Dec. 2014, Bandar Sunway, Selangor, Malaysia. (pp. 853-857). 10.1109/IEEM.2014.7058759 |
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| description |
In the process industry controlling the pH is considered to be one of the toughest tasks among the most commonly controlled variables. This is due to the nonlinear behavior of the pH and the time dependence of the nonlinearity, requiring an advanced controller. In this paper a multi-model nonlinear model predictive control (MMNMPC) scheme is applied to describe and handle the nonlinearities, were the multi-model description gives a piecewise linear description enabling a simple and swift computation of control moves. MPC implementation requires the knowledge, through measurement or by estimation, of the states of the neutralization system, both creating various problems. Here problem is addressed by including integral action in the controller to compensate for the unmeasured states. The MMNMPC combined with integral action is tested by simulation of a pH system in Matlab and the control structures were applied in Matlab/YALMIP showing good control performance. |
| format |
Conference or Workshop Item |
| author |
Hermansson, A. W. Syafiie, Syafiie |
| spellingShingle |
Hermansson, A. W. Syafiie, Syafiie Control of pH neutralization system using nonlinear model predictive control with I-controller |
| author_facet |
Hermansson, A. W. Syafiie, Syafiie |
| author_sort |
Hermansson, A. W. |
| title |
Control of pH neutralization system using nonlinear model predictive control with I-controller |
| title_short |
Control of pH neutralization system using nonlinear model predictive control with I-controller |
| title_full |
Control of pH neutralization system using nonlinear model predictive control with I-controller |
| title_fullStr |
Control of pH neutralization system using nonlinear model predictive control with I-controller |
| title_full_unstemmed |
Control of pH neutralization system using nonlinear model predictive control with I-controller |
| title_sort |
control of ph neutralization system using nonlinear model predictive control with i-controller |
| publisher |
IEEE (IEEE Xplore) |
| publishDate |
2014 |
| url |
http://psasir.upm.edu.my/id/eprint/39831/ |
| _version_ |
1643832538240647168 |
| score |
13.251813 |