使用适应性神经模糊控制器在电池可变性下对长物体进行空中操纵.
Praveen Kumar Muthusamy1,2, Mohammed Basheer Mohiuddin3,4, Anees Peringal5,6
1Khalifa University Center for Autonomous Robotic Systems (KUCARS), Khalifa University, Abu Dhabi, UAE. praveen.muthusamy@ku.ac.ae.
Scientific reports
|March 29, 2025
概括
本研究介绍了一个模块化的空中操纵系统,用于在具有挑战性的环境中精确地处理长物体. SO-BFBEL控制器显著提高了稳定性,减少了错误,提高了运营效率.
科学领域:
- 机器人和自动化机器人与自动化
- 土木工程应用 土木工程应用
- 空中飞机系统 飞机系统
背景情况:
- 空中操纵为狭窄空间中的任务提供了多功能解决方案,这对于土木工程和灾害响应至关重要.
- 现有的单臂或双臂系统面临着可扩展性和维护方面的挑战.
- 在不确定的条件下精确处理像管道这样的长物体仍然是一个重大挑战.
研究的目的:
- 提出基于无人机 (UAV) 的空中操纵系统,用于精确处理和运输长物体.
- 为提高可扩展性和可靠性,引入模块化双指抓柄设计.
- 为了评估SO-BFBEL控制器的性能与传统方法相比,以提高稳定性和精度.
主要方法:
- 开发一个模块化的双指抓手,用于基于无人机的空中操作.
- 实施SO-BFBEL (基于滑动模式的反错误学习) 控制器,以提高稳定性和精度.
- 对SO-BFBEL控制器与基于DNN-MRFT的PID和Fuzzy SMC控制器进行比较分析.
主要成果:
- 与传统控制器相比,SO-BFBEL控制器可将位置跟踪错误降低高达50%.
- SO-BFBEL控制器对风力干扰和电池放电波动进行了优异的补偿.
- 在操作任务中,SO-BFBEL控制器有助于节省电池寿命.
结论:
- 拟议的基于无人机的空中操纵系统具有模块化的抓手和SO-BFBEL控制器,为精确的长距离物体处理提供了可扩展和可靠的解决方案.
- SO-BFBEL控制器显著提高了系统的稳定性,精度和对抗环境干扰的稳定性.
- 该系统提高了运营效率并节省了电池寿命,为土木工程和灾害响应应用提供了成本效益优势.
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