Journal
ELECTRONICS
Volume 11, Issue 9, Pages -Publisher
MDPI
DOI: 10.3390/electronics11091337
Keywords
electric power steering; steering angle control; sliding mode control; sliding mode observer; autonomous vehicles
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This paper addresses the challenges associated with steering-angle control of electric power steering for autonomous vehicles. It proposes a variable gain-sliding mode steering-angle controller and develops a sliding mode observer to estimate the self-aligning moment disturbance and other disturbances. Simulation and experimental results demonstrate the stability and robustness of the proposed methods to the challenges mentioned.
This paper addresses the challenges associated with steering-angle control of electric power steering for autonomous vehicles, including steering model parameter uncertainty, dependency of self-aligning moment disturbance estimation on tire parameters, and compensation for the asymmetrical hysteresis behavior in the steering system caused by backlash in gears and static friction. A variable gain-sliding mode steering-angle controller is developed to deal with these challenges. Replacing the fixed gain with variable gain in the sliding mode controller solves two problems: it eliminates chattering, and it allows for automatic gain adjustment based on the maneuver and the size of the error, which eliminates the need for gain scheduling. Both fixed and variable gain-sliding mode controllers are derived and compared in simulations to prove the superiority of the variable gain controller. A sliding mode observer is developed to estimate the self-aligning moment disturbance without required information about the tire parameters, which makes it vehicle independent. The observer also treats the static friction as disturbance and estimates it along with any other disturbance, such as driver torque disturbance. The stability of both the controller and the observer is proven using Lyapunov stability theory. Simulation and experimental results proved the robustness of the presented methods to the above challenges.
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