Application of graphic processing unit in model predictive control
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This study seeks to pave the way for the implementation of a model predictive controller method using a Graphic Processing Unit (GPU). The GPU has been adapted and used as a real time co processor for Nonlinear Model Predictive Control (NMPC) algorithms, providing a means to improve the computational performance of the MPC algorithm in an economic manner. In this approach, a parallel version of Nelder-Mead simplex algorithm was used to solve MPC optimization problem. In order to show the effectiveness of the proposed approach, the implementation was applied in model predictive control of a crystallizer unit operation. The results show a considerable improvement in computational performance compared to standard CPU based implementation.
|Publication Type:||Journal Article|
|Murdoch Affiliation:||School of Engineering and Energy|
|Copyright:||© 2011 Elsevier B.V.|
|Notes:||21st European Symposium on Computer Aided Process Engineering|
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