Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/82414
Title: Image-based Visual Tracking Adaptive Control for Mobile Robots
Authors: Zou, Ying
Wen, Changyun
Shan, Mao
Guan, Mingyang
Keywords: wheels
actuators
Issue Date: 2016
Source: Zou, Y., Wen, C., Shan, M., & Guan, M. (2016). Image-based visual tracking adaptive control for mobile robots. 2016 14th International Conference on Control, Automation, Robotics & Vision (ICARCV).
Conference: 2016 14th International Conference on Control, Automation, Robotics & Vision (ICARCV)
Abstract: In this paper, we deal with the problem of image-based visual tracking for mobile robots. It is noted that the presence of actuator dynamics and the unknown target motion increases the complexity of the system model and makes the design of the controller more difficult. To solve this problem, we propose an adaptive control approach via utilizing backstepping technique and extended state observer (ESO). For the controller design, the adaptive technique is employed to estimate the bound of the target motion and the adaptive law is derived from the Lyapunov stability theory. We also adopt two ESOs to estimate and compensate for the disturbances affecting the mobile robot dynamics and the wheel actuator dynamics. It is shown that the proposed adaptive controller guarantees the boundness of all the signals in the closed-loop system and enables the tracking errors to exponentially converge to a compact set which is adjustable.
URI: https://hdl.handle.net/10356/82414
http://hdl.handle.net/10220/42307
DOI: 10.1109/ICARCV.2016.7838831
Schools: School of Electrical and Electronic Engineering 
Rights: © 2016 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Conference Papers

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