基于模糊逻辑的参数选择改进无人机路径跟踪算法

Q1 Mathematics
Pablo Garcia-Aunon , Matilde Santos Peñas , Jesus Manuel de la Cruz García
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引用次数: 20

摘要

为了控制无人机并使其沿预定轨迹飞行,需要一个高级控制器。根据控制算法,必须调整一个或多个参数,这些参数的值对性能有很大影响。在大多数工作中,这些参数都是常数。本文将模糊逻辑应用于控制律参数的选择,并与恒参数整定方法和另一种基于无人机运动方程分析的整定方法进行了比较。通过对四旋翼飞行器随机路径的仿真,证明了模糊整定律不仅是一种很好的可行解,而且具有通用性,可以适用于任何轨迹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameter selection based on fuzzy logic to improve UAV path-following algorithms

In order to steer an Unmanned Aerial Vehicle (UAV) and make it follow a desired trajectory, a high level controller is needed. Depending on the control algorithm, one or more parameters have to be tuned, having their values high impact on the performance. In most of the works, these parameters are taken as constant. In this paper, we apply fuzzy logic to select the parameters of the control law and compare this approach with the tuning by constant parameters and with another adjusting method based on the kinematic analysis of the equations of the UAV. After many simulations of the quadrotor following randomly generated paths, we have proved that the fuzzy tuning law is not only a good and feasible solution, but also more general as it can be applied to any trajectory.

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来源期刊
Journal of Applied Logic
Journal of Applied Logic COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
1.13
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: Cessation.
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