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Journal of Applied Sciences
  Year: 2009 | Volume: 9 | Issue: 18 | Page No.: 3219-3235
DOI: 10.3923/jas.2009.3219.3235
 
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Adaptive Feedback Linearization Control of Nonlinear Processes using Neural Network Based Approaches

F. Hourfar and K. Salahshoor

Abstract:
In this study, two different techniques for adaptive control of nonlinear chemical processes based on feedback linearization method are presented. The first technique utilizes a black-box modeling approach to completely model an unknown plant by an adaptive neural network whereas, the second technique focuses only on the difficult-to-model part or complicated part of the plant to identify a semi-mechanistic or grey-box model using an adaptive neural network. The remaining parts of the plant dynamics are obtained online using the combined first-principle model and special measuring methods. The performances of both adaptive control techniques have been demonstrated on a well-known Continuous Stirred Tank Reactor (CSTR) benchmark process to investigate their comparative capabilities.
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How to cite this article:

F. Hourfar and K. Salahshoor, 2009. Adaptive Feedback Linearization Control of Nonlinear Processes using Neural Network Based Approaches. Journal of Applied Sciences, 9: 3219-3235.

DOI: 10.3923/jas.2009.3219.3235

URL: https://scialert.net/abstract/?doi=jas.2009.3219.3235

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