DocumentCode
1584973
Title
Neural network based adaptive control of nonlinear plants using random search optimization algorithms
Author
Boussalis, Dhemetrios ; Wang, Shyh Jong
Author_Institution
Jet Propulsion Lab., California Inst. of Technol., Pasadena, CA, USA
fYear
1992
Firstpage
1152
Abstract
A method for utilizing artificial neural networks for direct adaptive control of dynamic systems with poorly known dynamics is presented. The neural network weights (controller gains) are adapted in real time using state measurements and a random search optimization algorithm. The results are demonstrated via simulation using two highly nonlinear systems
Keywords
adaptive control; neural nets; nonlinear dynamical systems; optimisation; search problems; artificial neural networks; controller gains; direct adaptive control; dynamic systems; highly nonlinear systems; nonlinear plants; random search optimization algorithm; state measurements; Adaptive control; Artificial neural networks; Control systems; Multi-layer neural network; Neural networks; Nonlinear control systems; Optimization methods; Propulsion; Space vehicles; Vehicle dynamics;
fLanguage
English
Publisher
ieee
Conference_Titel
Signals, Systems and Computers, 1992. 1992 Conference Record of The Twenty-Sixth Asilomar Conference on
Conference_Location
Pacific Grove, CA
ISSN
1058-6393
Print_ISBN
0-8186-3160-0
Type
conf
DOI
10.1109/ACSSC.1992.269118
Filename
269118
Link To Document