Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/201656
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dc.titleGENERALIZED SYSTEM IDENTIFICATION FOR NONLINEAR MODEL PREDICTIVE CONTROL
dc.contributor.authorEWAN CHEE JUN XIAN
dc.date.accessioned2021-09-30T18:01:04Z
dc.date.available2021-09-30T18:01:04Z
dc.date.issued2021-06-16
dc.identifier.citationEWAN CHEE JUN XIAN (2021-06-16). GENERALIZED SYSTEM IDENTIFICATION FOR NONLINEAR MODEL PREDICTIVE CONTROL. ScholarBank@NUS Repository.
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/201656
dc.description.abstractThis work articulates an overarching and integrated System Identification procedure for systematically deriving black-box nonlinear continuous-time and discrete-time multiple-input multiple-output system models for Nonlinear Model Predictive Control. This framework successfully identified both continuous-time and discrete-time black-box internal models for a highly nonlinear Continuous Stirred Tank Reactor system that enabled Nonlinear Model Predictive Controllers to achieve effective control in both servo and regulator problems across wider operating ranges, even with ~1% output measurement error. These controllers also had reasonable per-iteration times of ~0.1 seconds and ~1 second with the continuous- and discrete- time models, respectively. By demonstrating how such system models could be identified for Nonlinear Model Predictive Control without prior knowledge of system dynamics, this opens further possibilities for direct data-driven methodologies for model-based control which, in the face of process uncertainties or modeling limitations, allow rapid and stable control over a wider operating range.
dc.language.isoen
dc.subjectNonlinear model predictive control, black-box modeling, system identification, machine learning, industrial applications of process control
dc.typeThesis
dc.contributor.departmentCHEMICAL & BIOMOLECULAR ENGINEERING
dc.contributor.supervisorWang Xiaonan
dc.description.degreeMaster's
dc.description.degreeconferredMASTER OF ENGINEERING (FOE)
dc.published.stateUnpublished
Appears in Collections:Master's Theses (Open)

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