ROV浮游工作时由于存在系统模型不确定性和环境干扰导致跟踪效果不佳的问题，因此，提出一种参数变化的非奇异终端滑模自抗扰控制方法；首先，建立ROV的动力学模型；其次，利用非奇异终端滑模控制器代替了传统线性自抗扰的线性控制器，提高了系统的控制性能和抗干扰能力，考虑到引入参数过多问题利用梯度下降的RBF神经网络调整趋近率系数，通过李雅普诺夫定理证明了该系统的稳定性；最后，通过轨迹跟踪仿真实验与线性自抗扰对比，提高了系统响应过程的快速性和平稳性。
This paper proposes a non-singular terminal sliding mode active disturbance rejection control method with parameter variation caused by the uncertainty of the system model and environmental disturbance when the tracked underwater robot works floating. Secondly, a non-singular terminal sliding-mode controller is used to replace the traditional linear self-resisting linear controller to improve the control performance and anti-disturbance capability of the system. The convergence rate is adjusted by using a gradient-descent RBF neural network considering the problem of introducing too many parameters, and the stability of the system is proved by Lyapunov's theorem. Finally, the trajectory tracking simulation experiments are compared to linear self immunity, rapidity and smoothness of the response process of the system is improved.
2024,46(10): 87-91 收稿日期：2023-07-11
DOI：10.3404/j.issn.1672-7649.2024.10.015
分类号：TP23
作者简介：台立钢(1966-),男,博士,副教授,研究方向为计算机辅助设计与制造
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