Spatial Trajectory Tracking of Wall-Climbing Robot on Cylindrical Tank Surface Using Backstepping Sliding-Mode Control.
backstepping control
climbing robot
positioning
sliding-mode control
tank inspection
trajectory tracking
Journal
Micromachines
ISSN: 2072-666X
Titre abrégé: Micromachines (Basel)
Pays: Switzerland
ID NLM: 101640903
Informations de publication
Date de publication:
26 Feb 2023
26 Feb 2023
Historique:
received:
03
02
2023
revised:
24
02
2023
accepted:
25
02
2023
medline:
30
3
2023
entrez:
29
3
2023
pubmed:
30
3
2023
Statut:
epublish
Résumé
Wall-climbing robots have been well-developed for storage tank inspection. This work presents a backstepping sliding-mode control (BSMC) strategy for the spatial trajectory tracking control of a wall-climbing robot, which is specially designed to inspect inside and outside of cylindrical storage tanks. The inspection robot is designed with four magnetic wheels, which are driven by two DC motors. In order to achieve an accurate spatial position of the robot, a multisensor-data-fusion positioning method is developed. The new control method is proposed with kinematics based on a cylindrical coordinate system as the robot is moving on a cylindrical surface. The main purpose is to promote a smooth and stable tracking performance during inspection tasks, under the consideration of the robot's kinematic constraints and the magnetic restrictions of the adhesion system. The simulation results indicate that the proposed sliding mode controller can quickly correct the errors and global asymptotic stability is achieved. The prototype experimental results further validate the advancement of the proposed method; the wall-climbing robot can track both longitudinal and horizontal spatial trajectories stably with high precision.
Identifiants
pubmed: 36984954
pii: mi14030548
doi: 10.3390/mi14030548
pmc: PMC10059141
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Jiangsu Provincial Science and Technology Plan Project of China
ID : BE2022030776
Organisme : National Key Research and Development Program of China
ID : SQ2021YFF05002684
Références
IEEE Int Conf Rehabil Robot. 2011;2011:5975346
pubmed: 22275550