DocumentCode
700656
Title
Stable adaptive control with recurrent networks
Author
Kulawski, G.J. ; Brdys, M.A.
Author_Institution
Sch. of Electron. & Electr. Eng., Univ. of Birmingham, Birmingham, UK
fYear
1997
fDate
1-7 July 1997
Firstpage
1340
Lastpage
1345
Abstract
An adaptive control technique for nonlinear plants with immeasurable state is presented. It is based on a recurrent neural network employed as a dynamical model of the plant. Using this dynamical model, a feedback linearizing control is computed and applied to the plant. Parameters of the model are updated on line to allow for partially unknown and time varying plant. Stability of the scheme is shown theoretically and its performance is illustrated in simulations.
Keywords
adaptive control; feedback; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; stability; time-varying systems; dynamical model; feedback linearizing control; nonlinear plants; recurrent neural network; stability; stable adaptive control technique; time varying plant; unmeasurable state; Adaptation models; Computational modeling; Convergence; Lyapunov methods; Neural networks; Stability analysis; Trajectory; adaptive control; neural nets; nonlinear control;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (ECC), 1997 European
Conference_Location
Brussels
Print_ISBN
978-3-9524269-0-6
Type
conf
Filename
7082286
Link To Document