Title :
Neural network integration in control system structures: a case study towards intelligent control by neural network integration
Author :
Zaprianov, Jordan ; Atanasova, Tatiana
Author_Institution :
Inst. of Control & Syst. Res., Bulgarian Acad. of Sci., Sofia, Bulgaria
Abstract :
Neural networks techniques have been found to be useful for controlling highly uncertain, nonlinear and complex systems. The possibility of applying neural networks for modelling of unknown functions in dynamic environments has been demonstrated by several empirical studies. Allowing unknown nonlinearities in the system to be controlled we extend the class of uncertain systems that adaptive control techniques can be applied to. In the paper an integration of neural networks in the control systems is considered. Neural network application schemes are described. Some advantages of neural modelling and control are presented
Keywords :
adaptive control; feedforward neural nets; intelligent control; neurocontrollers; nonlinear systems; uncertain systems; adaptive control; complex systems; feedforward neural network; intelligent control; neural modelling; neurocontrol; nonlinear systems; nonlinearities; uncertain systems; Adaptive control; Artificial neural networks; Automatic control; Computer aided software engineering; Control systems; Intelligent control; Intelligent networks; Multi-layer neural network; Neural networks; Nonlinear control systems;
Conference_Titel :
Intelligent Control, 1997. Proceedings of the 1997 IEEE International Symposium on
Conference_Location :
Istanbul
Print_ISBN :
0-7803-4116-3
DOI :
10.1109/ISIC.1997.626446