A study of bicycle dynamics via system identification
CK Chen, TK Dao - 2010 International Symposium on …, 2010 - ieeexplore.ieee.org
This study investigates bicycle dynamic properties by using system identification
approaches. The nonlinear bicycle model with configuration parameters from a previously
developed benchmark model is studied. The roll angle of the bicycle is controlled at different
speeds to generate input-output data including steering torque, roll and steering angles. The
collected data are then used to identify the one-input two-output linear model by a prediction-
error identification method using parameterization in canonical state-space form. Numerous …
approaches. The nonlinear bicycle model with configuration parameters from a previously
developed benchmark model is studied. The roll angle of the bicycle is controlled at different
speeds to generate input-output data including steering torque, roll and steering angles. The
collected data are then used to identify the one-input two-output linear model by a prediction-
error identification method using parameterization in canonical state-space form. Numerous …
A study of bicycle dynamics via system identification approaches
TK Dao, CK Chen - Journal of the Chinese Institute of Engineers, 2012 - Taylor & Francis
This study investigates bicycle dynamic properties by using system identification
approaches. The non-linear bicycle model with configuration parameters from a previously
developed benchmark model is studied. The roll angle of the bicycle is controlled at different
speeds to generate input–output data including steering torque, roll, and steering angles.
The collected data are then used to identify the one-input two-output linear model by a
prediction-error identification method using parameterization in canonical state-space form …
approaches. The non-linear bicycle model with configuration parameters from a previously
developed benchmark model is studied. The roll angle of the bicycle is controlled at different
speeds to generate input–output data including steering torque, roll, and steering angles.
The collected data are then used to identify the one-input two-output linear model by a
prediction-error identification method using parameterization in canonical state-space form …
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