This article focuses on the practically adaptive safety tracking issue for the motor turntable of anti-drone systems subject to stochastic disturbances. Unlike existing research methods, the constraints issue of current for the motor turntable is fully considered to ensure the safety of the experimental environment. Specifically, the tangent function is employed for coordinate transformation as a means to obtain unconstrained variables, addressing current constraints. Meanwhile, chattering problems and stochastic disturbances are inevitable in the physical environment, potentially leading to wear and tear on actual systems and even instability. Furthermore, a novel adaptive fast finite-time safety algorithm has been proposed to address those problems for anti-drone systems, enabling precise strikes against the target. On this basis, an innovative fast finite-time controller has been successfully constructed that integrates the neural networks with special piecewise functions via the backstepping techniques. Therefore, the proposed controller can not only ensure the boundedness of all closed-loop system signals in probability but also avoid the singularity of the control signals. Finally, the superior performance of the proposed tracking algorithm is thoroughly demonstrated through a combination of hardware experiments and numerical simulations.

Publication:

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

http://dx.doi.org/10.1109/TIE.2026.3699881

Author:

Yafeng Xue

School of Cybersecurity, Northwestern Polytechnical University, Xi’an 710072, China

e-mail: xueyafeng@mail.nwpu.edu.cn

Zhen Wang

School of Cybersecurity, Northwestern Polytechnical University, Xi’an 710072, China

e-mail: w-zhen@nwpu.edu.cn

Hao Xu

Key Laboratory of Systems and Control, Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China

e-mail: haoxu2021@mail.nwpu.edu.cn

Dengxiu Yu

School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an 710072, China

e-mail: yudengxiu@nwpu.edu.cn