Estimation of the mechanical state variables of the two-mass system using fuzzy adaptive Kalman filter - Experimental study

Author

Drozdz, Krzysztof

Author_Institution

Dept. of Electr. Machines, Drives & Meas., Wroclaw Univ. of Technol., Wrocław, Poland

fYear

2015

fDate

24-26 June 2015

Firstpage

455

Lastpage

459

Abstract

This paper investigates the application of fuzzy adaptive Kalman Filter for mechanical state variable and parameter estimation of the drive system with elastic joint. The adaptive state-space controller, which coefficients are retuned according to the estimation parameter provided by Kalman filter, is selected to control the two-mass system effectively. Selected elements of covariance matrix Q are retuned by proposed adaptation law. Additional fuzzy element is used to modified the control law in order to decrease estimation error of the plant. The effectiveness of the proposed approach is investigated under variety of experimental tests.

Keywords

adaptive Kalman filters; adaptive control; covariance matrices; drives; fuzzy control; parameter estimation; state-space methods; adaptation law; adaptive state-space controller; control law; covariance matrix; drive system; elastic joint; fuzzy adaptive Kalman filter; fuzzy element; mechanical state variables; parameter estimation; two-mass system; Adaptive systems; Covariance matrices; Fuzzy systems; Kalman filters; Shafts; Torque; Transient analysis; Kalman filter; adaptive system; fuzzy system; torsional vibration; two-mass system;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetics (CYBCONF), 2015 IEEE 2nd International Conference on

Conference_Location

Gdynia

Print_ISBN

978-1-4799-8320-9

Type

conf

DOI

10.1109/CYBConf.2015.7175977

Filename

7175977