Optimization-based Tuning of Nonlinear Model Predictive Control with State Estimation
dc.contributor.author | Ali, Emad | en_US |
dc.contributor.author | Zafiriou, E. | en_US |
dc.contributor.department | ISR | en_US |
dc.date.accessioned | 2007-05-23T09:54:07Z | |
dc.date.available | 2007-05-23T09:54:07Z | |
dc.date.issued | 1993 | en_US |
dc.description.abstract | Nonlinear Model Predictive Controllers determine appropriate control actions by solving an on-line optimization problem. A nonlinear process model is utilized for on-line prediction, making such algorithms particularly appropriate for the control of chemical reactors. The algorithm presented in this paper incorporates an Extended Kalman Filter, which allows operations around unstable steady-state points. The paper proposes a formalization of the procedure for tuning the several parameters of the control algorithm. This is accomplished by specifying time-domain performance criteria and using an interactive multi- objective optimization package off-line to determine parameter values that satisfy these criteria. Three reactor examples are used to demonstrate the effectiveness of the proposed on-line algorithm and off-line procedure. | en_US |
dc.format.extent | 1194478 bytes | |
dc.format.mimetype | application/pdf | |
dc.identifier.uri | http://hdl.handle.net/1903/5396 | |
dc.language.iso | en_US | en_US |
dc.relation.ispartofseries | ISR; TR 1993-51 | en_US |
dc.subject | chemical process control | en_US |
dc.subject | optimization | en_US |
dc.subject | predictive control | en_US |
dc.subject | estimation | en_US |
dc.subject | nonlinear systems | en_US |
dc.subject | optimal control | en_US |
dc.subject | optimization | en_US |
dc.subject | Chemical Process Systems | en_US |
dc.title | Optimization-based Tuning of Nonlinear Model Predictive Control with State Estimation | en_US |
dc.type | Technical Report | en_US |
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