基于生物神经动力学的无人潜航器混合跟踪控制策略

IF 1.5 Q3 AUTOMATION & CONTROL SYSTEMS
Zhe Xu, Tao Yan, Simon X. Yang, S. Andrew Gadsden
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引用次数: 1

摘要

跟踪控制一直是机器人领域的一个重要研究课题。提出了一种基于仿生神经动力学模型的无人潜航器混合控制策略。首先提出了一种增强的反步运动控制策略,以避免急剧的速度跳跃,并提供相对于传统方法平滑的速度命令。然后,提出了一种新的滑模控制方法,该方法能够提供平滑连续的无抖振转矩指令。在对比研究中,所提出的组合混合控制策略确保了控制信号的平滑性,这在实际应用中至关重要,特别是对于需要在复杂水下环境中运行的UUV。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A hybrid tracking control strategy for an unmanned underwater vehicle aided with bioinspired neural dynamics

A hybrid tracking control strategy for an unmanned underwater vehicle aided with bioinspired neural dynamics

Tracking control has been a vital research topic in robotics. This paper presents a novel hybrid control strategy for an unmanned underwater vehicle (UUV) based on a bioinspired neural dynamics model. An enhanced backstepping kinematic control strategy is first developed to avoid sharp velocity jumps and provides smooth velocity commands relative to conventional methods. Then, a novel sliding mode control is proposed, which is capable of providing smooth and continuous torque commands free from chattering. In comparative studies, the proposed combined hybrid control strategy has ensured control signal smoothness, which is critical in real-world applications, especially for a UUV that needs to operate in complex underwater environments.

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来源期刊
IET Cybersystems and Robotics
IET Cybersystems and Robotics Computer Science-Information Systems
CiteScore
3.70
自引率
0.00%
发文量
31
审稿时长
34 weeks
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