Aerial manipulation of long objects using adaptive neuro-fuzzy controller under battery variability

利用自适应神经模糊控制器在电池容量变化下对长物体进行空中操控

阅读:1

Abstract

Aerial manipulation provides adaptable solutions for executing tasks in constrained environments, particularly in civil engineering and disaster response. This paper presents a UAV-based aerial manipulation system for the precise handling and transportation of long objects, such as pipes, in uncertain conditions. Compared to single- or dual-arm systems, which are difficult to scale and maintain, the proposed design features a modular two-finger gripper, enhancing scalability and reliability while reducing mechanical complexity. To address challenges such as positional drift, which can compromise mission success, the system employs a SO-BFBEL controller controller to enhance stability and precision and it is compared with DNN-MRFT-based PID and Fuzzy SMC controller. Experimental results demonstrate that the SO-BFBEL controller reduces the position tracking error up to 50% and compensates for wind disturbances and battery discharge fluctuations more effectively than conventional methods. Additionally, the SO-BFBEL controller can help to conserve battery life during manipulation phases which can boost the operational efficiency without incurring any additional costs.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。