基于模糊SMO和执行器故障检测控制算法的消费电子增强无人机农场跟踪系统

IF 10.9 2区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Hazrat Bilal;Muhammad Shamrooz Aslam;Yibin Tian;Inam Ullah;Sarra Ayouni;Athanasios V. Vasilakos
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引用次数: 0

摘要

农业机器人的采用彻底改变了现代农业操作,从作物监测到自动收获,大大提高了生产力。由于农业机器人的快速发展及其与智能农业实践的整合,本研究提出了一种使用四轴无人机的小麦农场自主轨迹跟踪系统。为了解决执行器故障检测问题,包括卡故障和部分效率损失,引入了TSF- $H^{\infty }$ - smo (Takagi-Sugeno Fuzzy-based $H^{\infty }$滑模观测器)故障检测框架。该方法首先推导了集成不确定性项的TSF (Takagi-Sugeno Fuzzy)姿态控制模型,该模型由无人机的原始非线性动力学构造,并通过四个平衡位置的局部线性模型进行逼近。随后,将执行器故障模型集成到考虑执行器故障的TSF-UAV综合模型中。然后利用矩阵坐标变换设计TSF- $H^{\infty }$ - smo,实现精确的故障检测。通过对TSF- uav模型在SISO(单输入单输出)执行器故障场景下的仿真,评估了TSF- $H^{\infty }$ - smo的故障检测能力。实验结果验证了该系统的有效性,证明了该系统能够准确、快速地检测出一系列执行器故障。分析揭示了状态变化的幅度与故障严重程度之间的比例关系,这归因于系统状态与执行机构襟翼之间的相互作用。这种方法强调了在农业应用中部署基于无人机的自主故障检测和轨迹跟踪系统的潜力。此外,集成这种先进的容错控制算法为消费者技术应用带来了希望,在这些应用中,精度、可靠性和鲁棒性对提高系统性能和运行效率至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Consumer Electronics-Enhanced UAV System for Agricultural Farm Tracking With Fuzzy SMO and Actuator Fault Detection Control Algorithms
The adoption of agricultural robots, or agrobots, has revolutionized modern farming operations, ranging from crop monitoring to automated harvesting, significantly boosting productivity. Motivated by the rapid advancements in agrobots and their integration into smart agricultural practices, this study proposes an autonomous trajectory tracking system for wheat farms using quadcopter UAVs. To address actuator fault detection, including stuck faults and partial loss of efficiency, a TSF- $H^{\infty }$ -SMO (Takagi-Sugeno Fuzzy-based $H^{\infty }$ Sliding Mode Observer) fault detection framework is introduced. The approach initiates with the derivation of a TSF (Takagi-Sugeno Fuzzy) attitude control model that integrates an uncertainty term, constructed from the original nonlinear dynamics of the UAV and approximated through local linear models at four equilibrium positions. An actuator fault model is subsequently integrated to develop a comprehensive TSF-UAV model, accounting for actuator faults. The TSF- $H^{\infty }$ -SMO is then designed using matrix coordinate transformation to enable precise fault detection. The fault detection capabilities of the TSF- $H^{\infty }$ -SMO are evaluated through simulations on the TSF-UAV model under SISO (single-input single-output) actuator fault scenarios. The experimental results validate the proposed system, demonstrating its ability to detect a range of actuator faults accurately and promptly. The analysis reveals a proportional relationship between the amplitude of the state change and the severity of the fault, attributed to the interaction between system states and actuator flaps. This approach underscores the potential for deploying autonomous UAV-based fault detection and trajectory tracking systems in agricultural applications. Furthermore, integrating such advanced fault-tolerant control algorithms holds promise for consumer technology applications, where precision, reliability, and robustness are critical to enhancing system performance and operational efficiency.
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来源期刊
CiteScore
7.70
自引率
9.30%
发文量
59
审稿时长
3.3 months
期刊介绍: The main focus for the IEEE Transactions on Consumer Electronics is the engineering and research aspects of the theory, design, construction, manufacture or end use of mass market electronics, systems, software and services for consumers.
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