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Model predictive control based on neural identification method

โœ Scribed by M. Sugisaka; M. Ino


Publisher
Elsevier Science
Year
1994
Tongue
English
Weight
600 KB
Volume
27
Category
Article
ISSN
0898-1221

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โœฆ Synopsis


This paper presents a new approach to model predictive control (denoted as MPC)

based on a new identifier utilizing the artificial neural network system (denoted as ANNS) with tapped delay lines added to the input layer of the ANNS.

The identifier uses the back-propagation method in order to minimize the errors between the output of the ANNS and the output of the system to be controlled.

The numerical simulation studies show that the neural identifiers have robustness in the change of operating conditions and circumstances and, hence, that the control performances of the MPC are quite satisfactory.


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