A genetic algorithm for the tuning of a discrete adaptive observer implemented on an IBM head/disk assembly

Author

Thein, May-Win L. ; Rendon, Thomas ; Misawa, Eduardo A.

Author_Institution

Sch. of Mech. & Aerosp. Eng., Oklahoma State Univ., Stillwater, OK, USA

Volume

1

fYear

1999

fDate

1999

Firstpage

164

Abstract

This paper presents the application of a discrete adaptive observer (DAO) to an IBM head/disk assembly system. Because of the difficulties in tuning, a genetic algorithm is implemented off-line to obtain optimal observer parameters for the DAO. Simulations show that the genetic algorithm is successful in choosing appropriate observer gains. Furthermore, as a result of these optimal gains, the observer state and parameter estimates converge accurately and quickly

Keywords

adaptive estimation; convergence; disc drives; discrete systems; genetic algorithms; observers; parameter estimation; IBM head/disk assembly; discrete adaptive observer tuning; genetic algorithm; observer parameter estimate convergence; observer state estimate convergence; optimal observer parameters; Aerospace engineering; Assembly systems; Asymptotic stability; Automatic control; Convergence; Genetic algorithms; Observers; Optimal control; Parameter estimation; State estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Applications, 1999. Proceedings of the 1999 IEEE International Conference on

Conference_Location

Kohala Coast, HI

Print_ISBN

0-7803-5446-X

Type

conf

DOI

10.1109/CCA.1999.806170

Filename

806170