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Multivariable averaging level control Sidhu, Manpreet S.
Abstract
This thesis studies the multivariable averaging level control problem by developing and comparing various controller design techniques. Due to obvious safety and economic considerations, the level of a surge tank must never be allowed to overflow or become empty, while the flow rate constraints must be satisfied. Hence, the main emphasis of the thesis is on the study of constrained controller design techniques. Multivariable design techniques such as decentralized, decoupled and full multivariable control are studied. The special structure of the system model allows for a constant decoupling matrix over all frequencies. This significantly simplifies the decoupled controller design. In full multivariable control, constrained Model Based Predictive Control (MPC) is utilized as it is able to naturally incorporate system constraints. Various cost function formulations which lead to either Quadratic or Linear Programming optimizations are presented and compared. The drawback of incorporating a terminal constraint set in MPC design is also studied. A novel mixed norm MPC algorithm that removes the requirement for using a terminal constraint set is proposed. MPC based on QP optimization is shown to provide the best results. The nonsmooth behaviour of MPC under LP optimization is also discussed. Finally, the practicality of some computationally-friendly techniques is assessed on a lab scale two-tank apparatus. The control algorithms are implemented in real-time using MatLab and dSpace.
Item Metadata
Title |
Multivariable averaging level control
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2003
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Description |
This thesis studies the multivariable averaging level control problem by developing and comparing various controller design techniques. Due to obvious safety and economic considerations, the level of a surge tank must never be allowed to overflow or become empty, while the flow rate constraints must be satisfied. Hence, the main emphasis of the thesis is on the study of constrained controller design techniques. Multivariable design techniques such as decentralized, decoupled and full multivariable control are studied. The special structure of the system model allows for a constant decoupling matrix over all frequencies. This significantly simplifies the decoupled controller design. In full multivariable control, constrained Model Based Predictive Control (MPC) is utilized as it is able to naturally incorporate system constraints. Various cost function formulations which lead to either Quadratic or Linear Programming optimizations are presented and compared. The drawback of incorporating a terminal constraint set in MPC design is also studied. A novel mixed norm MPC algorithm that removes the requirement for using a terminal constraint set is proposed. MPC based on QP optimization is shown to provide the best results. The nonsmooth behaviour of MPC under LP optimization is also discussed. Finally, the practicality of some computationally-friendly techniques is assessed on a lab scale two-tank apparatus. The control algorithms are implemented in real-time using MatLab and dSpace.
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Extent |
4003979 bytes
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Genre | |
Type | |
File Format |
application/pdf
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Language |
eng
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Date Available |
2009-10-28
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Provider |
Vancouver : University of British Columbia Library
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Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
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DOI |
10.14288/1.0065517
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2003-05
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Campus | |
Scholarly Level |
Graduate
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Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.