Abstract
A controller that combines the main characteristics and advantages of three different control methodologies is proposed for the control of systems with nonlinearities and uncertainties. A neural network predictive control approach is implemented modifying the output of a controller with a fuzzy logic structure that uses type-2 fuzzy sets. Neural networks are also used to optimize the membership function parameters. The proposed controller is tested by simulation for the control of a bioreactor characterized by bifurcation and parameter uncertainty.
Lingua originale | English |
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Pagine | 1203-1208 |
Numero di pagine | 6 |
Stato di pubblicazione | Published - 2009 |
All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)