控制无人驾驶车辆用于海洋环境传感的轨迹
Tegen Eyasu Derbew1, Nak Yong Ko1, Sung Hyun You2
1Interdisciplinary Program in IT-Bio Convergence Systems, Department of Electronic Engineering, Chosun University, Gwangju 61452, Republic of Korea.
Sensors (Basel, Switzerland)
|February 24, 2024
概括
一个新的强大的离散时间超扭转控制器 (DSTA) 增强了自主地表车辆的导航. 它在动态的海洋环境中最大限度地减少了轨迹误差,超过了传统的方法.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统工程 控制系统工程
- 海洋工程 海洋工程
背景情况:
- 自主地表车辆 (ASV) 对海洋环境传感至关重要.
- 在动态的海洋条件下 (海流,海浪,风) 导航ASV需要强大的轨迹控制.
- 现有的控制器与海洋环境的复杂性和轨迹错误作斗争.
研究的目的:
- 为ASV轨迹跟踪提出一个强大的离散时间超扭转二级滑动模式控制器 (DSTA).
- 为了提高控制器的稳定性,并最大限度地减少聊天效应.
- 使用遗传算法 (GA) 来优化控制器收益.
主要方法:
- 使用积分近似的ASV模型的分离化,将干扰视为干扰.
- 使用时间延迟估计器 (TDE) 估计扰动,以提高稳定性.
- 通过遗传算法 (GA) 优化控制器收益,最大限度地减少跟踪错误和控制能量.
- 使用利亚普诺夫方法进行稳定性分析.
主要成果:
- 拟议的GA调节的DSTA控制器与DSMR和启发式调节的DSTA相比,显示出更高的轨迹跟踪精度.
- 控制器有效地抑制了聊天效应.
- 在有外界干扰和没有外界干扰的模拟中证实了强大的性能.
结论:
- 在具有挑战性的海洋环境中,GA-DSTA为ASV轨道控制提供了强大而有效的解决方案.
- TDE显著提高了稳定性,允许控制器获得较小的收益.
- 拟议的控制器在跟踪精度和声减弱方面表现优于现有方法.
关键词:
利亚普诺夫稳定性的稳定性聊天聊天聊天聊天聊天聊天估计估计估计的估计.遗传算法是一种遗传算法.海洋海洋的海洋海洋的海洋感应感应感应 感应感应滑动模式控制器的滑动模式控制器随着轨迹的跟随轨迹.车辆 车辆 车辆 车辆 车辆更多相关视频
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