DocumentCode
1707914
Title
Comparison of CMAC controller weight update laws
Author
Kraft, L.G. ; An, Edgar ; Campagna, D.P.
Author_Institution
Dept. of Electr. & Comput. Eng., New Hampshire Univ., Durham, NH, USA
fYear
1989
Firstpage
1746
Abstract
A modeling technique that allows direct analysis of stability and convergence properties for control systems using the cerebellar model articulation controller (CMAC) neural network approach is presented. Two different network weight-updating methods are modeled and compared. The first technique updates the weights after each training sequence. The second method updates sequentially during each control cycle. Results favor sequential updating. In both weight methods the CMAC method can be made unstable
Keywords
brain models; control system analysis; neural nets; stability; CMAC controller weight update laws; cerebellar model articulation controller; convergence; neural network; stability; Control system synthesis; Control systems; Convergence; Eigenvalues and eigenfunctions; Equations; Large-scale systems; Matrices; Neural networks; Stability analysis; Weight control;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
Conference_Location
Tampa, FL
Type
conf
DOI
10.1109/CDC.1989.70451
Filename
70451
Link To Document