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This paper proposes a backlash control algorithm using Terminal Iterative Learning Control (TILC) in the angle domain. The proposed method addresses the issue of control time variation in the Iterative Learning Control (ILC) method, which makes it impractical for vehicle control. By controlling backlash in the angle domain, the control interval remains the same for each iteration. The backlash impact is proportional to the velocity at the end of the backlash mode. However, by bringing the reference value nearer to zero, the impact was mitigated. Additionally, the utilization of TILC enhances its resilience to sensor noise. The proposed method is evaluated through simulations and experimental results, demonstrating its practical applicability to vehicles and high accuracy in various initial conditions. This paper provides a novel approach to backlash control in-vehicle systems, contributing to the advancement of control methods for improved ride comfort and safety.
Kim et al. (Sun,) studied this question.
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