Application of model predictive control
Model Predictive Control (MPC) is an advanced control technology and appeared in industry as an effective control to deal with multivariable constrained control problems. MPC is the class of control algorithm that uses directly an explicit and separately identifiable model. In this project, the mult...
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sg-ntu-dr.10356-188092023-07-04T15:25:19Z Application of model predictive control Nandar Lynn Ling Keck Voon School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Model Predictive Control (MPC) is an advanced control technology and appeared in industry as an effective control to deal with multivariable constrained control problems. MPC is the class of control algorithm that uses directly an explicit and separately identifiable model. In this project, the multi-zone bake plate from post-exposure bake step in lithography is used as an application of model predictive control to show the work of MPC controller and the ser point tracking performance of MOC controller. In this study, the MPC controller is designed and implemented on the three-zone bake plate. Based on the heat transfer theory and energy balance equations, a model for the three-zone bake plate is derived and parameter estimation of three-zone bake plate is carried out to obtain the accurate and realistic model of the three-zone bake plate system. Them MPC controller is designed using the constraint MPC optimization criterion and the simulation scenarios of Constraint MPC are described to study the work of MPC controller. Then, the implementation of Constraint MPC on the three-zone bake plate is done and proposed to verify the working of MPC controller experimentally. The proposed constraint MPC is successfully applied to the multivariable system, the three-zone bake plate and the optimal solution is resulted in while the system is processing with the presence of the input power constraint. Master of Science (Computer Control and Automation) 2009-07-20T02:47:53Z 2009-07-20T02:47:53Z 2008 2008 Thesis http://hdl.handle.net/10356/18809 en 64 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering Nandar Lynn Application of model predictive control |
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Model Predictive Control (MPC) is an advanced control technology and appeared in industry as an effective control to deal with multivariable constrained control problems. MPC is the class of control algorithm that uses directly an explicit and separately identifiable model. In this project, the multi-zone bake plate from post-exposure bake step in lithography is used as an application of model predictive control to show the work of MPC controller and the ser point tracking performance of MOC controller. In this study, the MPC controller is designed and implemented on the three-zone bake plate.
Based on the heat transfer theory and energy balance equations, a model for the three-zone bake plate is derived and parameter estimation of three-zone bake plate is carried out to obtain the accurate and realistic model of the three-zone bake plate system. Them MPC controller is designed using the constraint MPC optimization criterion and the simulation scenarios of Constraint MPC are described to study the work of MPC controller. Then, the implementation of Constraint MPC on the three-zone bake plate is done and proposed to verify the working of MPC controller experimentally. The proposed constraint MPC is successfully applied to the multivariable system, the three-zone bake plate and the optimal solution is resulted in while the system is processing with the presence of the input power constraint. |
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Ling Keck Voon |
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Ling Keck Voon Nandar Lynn |
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Theses and Dissertations |
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Nandar Lynn |
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Nandar Lynn |
title |
Application of model predictive control |
title_short |
Application of model predictive control |
title_full |
Application of model predictive control |
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Application of model predictive control |
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Application of model predictive control |
title_sort |
application of model predictive control |
publishDate |
2009 |
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http://hdl.handle.net/10356/18809 |
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1772828178146918400 |