Multiple model predictive control of nonlinear pH neutralization system
In this paper the control of nonlinear systems using linear models is studied. The control strategy utilizes a piecewise linear description of the process, considered the model bank. The model bank is then combined at each sampling interval, through the application of a Bayesian weight calculator, t...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2010
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| Online Access: | http://psasir.upm.edu.my/id/eprint/69604/1/Multiple%20model%20predictive%20control%20of%20nonlinear%20pH%20neutralization%20system.pdf |
| Summary: | In this paper the control of nonlinear systems using linear models is studied. The control strategy utilizes a piecewise linear description of the process, considered the model bank. The model bank is then combined at each sampling interval, through the application of a Bayesian weight calculator, to render a single linear model describing the system. The linear model is used in a model predictive control (MPC) setting to render the optimal control move. The performance of the setup is simulated for a pH neutralization process, which demonstrates a good following of setpoint changes and quick reduction of oscillations. |
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