2023
DOI: 10.1109/access.2022.3166816
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Trajectory Tracking Strategy for Sliding Mode Control With Double Closed-Loop for Lawn Mowing Robot Based on ESO

Abstract: The mowing robots work with a multivariable strong coupling underactuated system that is mostly troubled by difficulty controlling and unsatisfactory accuracy. Especially, the frequent external disturbances and parameter changes are likely to get missed and heavy cutting. In this paper, a new trajectory tracking control method based on extended state observer (ESO) is introduced with a particular focus on dual closed-loop sliding mode. Firstly, from the perspective of kinematics, a speed assistant controller w… Show more

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Cited by 6 publications
(2 citation statements)
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References 41 publications
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“…The ideal model is often theoretical and may change during operation, making real-time adjustment of PID parameters challenging. Consequently, the sliding mode control algorithm has emerged as a viable alternative [5][6][7][8]. In [9], a controller is developed based on the position and heading errors of a mobile robot to enable the stable tracking of circular and straight paths despite significant tracking errors and external disturbances.…”
Section: Introductionmentioning
confidence: 99%
“…The ideal model is often theoretical and may change during operation, making real-time adjustment of PID parameters challenging. Consequently, the sliding mode control algorithm has emerged as a viable alternative [5][6][7][8]. In [9], a controller is developed based on the position and heading errors of a mobile robot to enable the stable tracking of circular and straight paths despite significant tracking errors and external disturbances.…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, tracking control for nonlinear systems has always been investigated for many real-world plants in practices, such as unmanned aerial vehicles [1], [2], robots [3], and quadrotors [4], [5]. To realize the performance of tracking, massive various control algorithms are employed for tracking control problems, including backstepping control [6], sliding model control [7], [8] and model predictive control [9].…”
Section: Introductionmentioning
confidence: 99%