LMS identification of systems with dynamics and an output deadzone

Author

Rekow, Andrew ; Jones, Vincent K. ; Parkinson, Bradford

Author_Institution

Stanford Univ., CA, USA

Volume

5

fYear

1998

fDate

21-26 Jun 1998

Firstpage

2770

Abstract

A system that extends traditional FIR filter adaptive system identification and control for use with systems that include an actuator deadzone has been developed. This method automatically identifies both the system´s dynamic and deadzone components. Nearly optimal performance is achieved utilizing a modified version of the least mean square error minimization scheme. From the identified model, a stable feedforward inverse controller that linearizes the system is quickly and reliably obtained

Keywords

FIR filters; adaptive control; adaptive filters; adaptive systems; filtering theory; identification; least mean squares methods; FIR filter adaptive system control; FIR filter adaptive system identification; actuator deadzone; least mean square error minimization scheme; least mean square identification; nearly optimal performance; output deadzone; Actuators; Adaptive control; Adaptive systems; Automatic control; Control systems; Finite impulse response filter; Least squares approximation; Mean square error methods; Programmable control; System identification;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 1998. Proceedings of the 1998

Conference_Location

Philadelphia, PA

ISSN

0743-1619

Print_ISBN

0-7803-4530-4

Type

conf

DOI

10.1109/ACC.1998.688358

Filename

688358