Abstract
In this article, the attitude control problem of a new-designed aerial trees-pruning robot is addressed. During the tree cutting process, the aerial trees-pruning robot will be disturbed by unknown external disturbances. At the same time, the model uncertainties will also affect the attitude controller. To overcome the above problems, an attitude controller is designed with a nonsingular fast terminal sliding mode method. First, the extended state observer is designed to estimate the modeling uncertainties and unknown disturbances. Then, the extended state observer-based nonsingular fast terminal sliding mode controller can make the tracking error of the attitude converge to zero in a finite time. Finally, a control allocation matrix switching strategy is proposed to solve the problem of the change of the aerial robot model in the cutting process. The final simulation and experimental results show that the extended state observer-based nonsingular fast terminal sliding mode controller designed in this article has good attitude control performance and can effectively overcome the modeling uncertainties and unknown disturbances. The attitude controller and control allocation matrix switching strategy ensure that the attitude angles of the aerial robot can quickly track the reference signals.
Highlights
The tree barrier cleanup tasks, near the highvoltage lines, are almost conducted by man with simple tools.[1,2] the tree barrier cleanup task, especially in complex environments, has brought great challenges to staff who are responsible for the tree barrier cleanup
When the saw blade came into contact with the tree, the control allocation matrix was switched in time to ensure the attitude stability of the aerial robot during the cutting process
To overcome the uncertainties of the inertial matrix and unknown disturbances, the attitude controller is designed by using the nonsingular fast terminal sliding mode (NFTSM) method and the extended state observer (ESO)
Summary
Qiuyan Zhang[1], Zhong Yang[2,3], Shaohui Wang2,3 , Yuhong Jiang[4], Changliang Xu2,3, Hao Xu2,3 and Xiangrong Xu5
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