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State Estimation of a Micro DC-Brushed Motor

Author(s):

M. Roggo
Conference/Journal:

Semester Thesis, FS14 (10306)
Abstract:

In this thesis we investigate the possibility to measure and estimate the wheel speed of a 1:43 scale ORCA race car. To achieve this, a wheel speed sensor is build and the encoder signal evaluation is implemented on the onboard micro-controller. In a second step, a nonlinear motor model is derived, which models the not correctly working H-bridge. The motor model is then identified based on different experiments and successfully cross validated. Based on the model, a Kalman filter is designed which is used to filter the noisy measurements. The performance of the filter is evaluated in the load free nominal case and under a load torque disturbance. Lastly we present preliminary results on a back-EMF wheel speed estimator, which suggest that there is no need for a wheel speed sensor, even under a unknown load disturbance.

Year:

2014
Type of Publication:

(13)Semester/Bachelor Thesis
Supervisor:

A. Liniger

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% Autogenerated BibTeX entry
@PhdThesis { Xxx:2014:IFA_4847
}
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