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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ravi, V.R. Thyagarajan, T. Darshini, M.M. |
| Copyright Year | 2011 |
| Abstract | Model predictive control (MPC) has become the leading form of advanced multivariable control in the chemical process industry. The objective of this work is to introduce a multiple model adaptive control strategy for multivariable MPC. The method of approach is to design multiple linear MPC controllers. This strategy maintains performance of multiple linear MPC controllers over a wide range of operating levels. One important contribution is that the strategy combines several multiple linear MPC controllers, each with their own linear state space model describing process dynamics at a specific level of operation. One of the linear MPC controller output is selected as multiple model adaptive controller's output based on the current value of the measured process variable. The tuning parameters for the linear MPC controller are obtained using Genetic Algorithm (GA). The capabilities of the multiple model adaptive strategy for MPC controller are investigated on Two Tank Conical Interacting System (TTCIS) through computer simulation. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 1354102 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781612847658 |
| e-ISBN | 9781612847641 |
| DOI | 10.1109/PACC.2011.5978896 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-20 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Industries Adaptation models Computational modeling Process control Predictive models Valves Mathematical model |
| Content Type | Text |
| Resource Type | Article |
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