DocumentCode
2954195
Title
Genetic algorithms for multiobjective predictive control
Author
Laabidi, Kaouther ; Bouani, Faouzi
Author_Institution
High Inst. of Appl. Sci. & Technol., Mateur, Tunisia
fYear
2004
fDate
2004
Firstpage
149
Lastpage
152
Abstract
Control of nonlinear uncertain dynamical systems is considered. The artificial neural networks (ANNs) are used to model the process. For each operating level an ANN is determined. The model predictive type of controller is designed that utilizes a set of ANN model and employs the input constraints. The nondominated sorting genetic algorithm (NSGA) is applied to solve the multiobjective optimization problem. The proposed control schema is applied to a numerical example and the simulation results are included.
Keywords
genetic algorithms; neurocontrollers; nonlinear control systems; predictive control; time-varying systems; uncertain systems; artificial neural networks; multiobjective optimization problem; multiobjective predictive control; nondominated sorting genetic algorithm; nonlinear uncertain dynamical systems; Artificial neural networks; Control systems; Genetic algorithms; Linear systems; Multilayer perceptrons; Predictive control; Predictive models; Sorting; Uncertain systems; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Communications and Signal Processing, 2004. First International Symposium on
Print_ISBN
0-7803-8379-6
Type
conf
DOI
10.1109/ISCCSP.2004.1296240
Filename
1296240
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