| ADAPTIVE STEERING ANGLE CONTROLLER FOR AUTONOMOUS VEHICLES IN THE PRESENCE OF PARAMETER UNCERTAINTY AND DISTURBANCES
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| Lubna Khasawneh , Manohar Das |
| Oakland University |
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| ABSTRACT |
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This paper addresses the problem of controlling the electric power steering angle for autonomous vehicles in
the presence of model parameter uncertainty and disturbances. Usually, the electric power steering manufacturer provides it
as a black box to the automotive companies and does not provide the model or the model parameters. Identifying those
parameters is a time-consuming process that requires a special vehicle setting, and does not always give accurate results.
Inaccuracies on those parameters deteriorate the behavior of the model-based controller that is using them. To overcome
those problems, an adaptive backstepping steering angle controller is designed, which assumes the steering model parameters
are unknown and develops parameter update laws to estimate them. Adaptive laws are also developed to estimate the
disturbance resulting from self-aligning moment. Usually, self-aligning moment estimation requires tire parameters
knowledge. In the adaptive backstepping method, it is treated as disturbance and no knowledge of tire parameters is required
in order to estimate it. Coulomb friction and static friction are considered as disturbances and estimated together with the
self-aligning moment disturbance. The performance of the proposed method was validated with numerical simulation. |
| Key Words:
Adaptive backstepping control, Electric power steering, Autonomous vehicles, Steering angle control
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Corresponding Author.
Lubna Khasawneh , Email. 
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