拖拉机用带 PID 项的无模型自适应预测路径跟踪控制器

IF 4.4 1区 农林科学 Q1 AGRICULTURAL ENGINEERING Biosystems Engineering Pub Date : 2024-04-23 DOI:10.1016/j.biosystemseng.2024.04.009
Jin Cheng , Bingli Zhang , Chengbiao Zhang , Yangyang Zhang , Gan Shen
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引用次数: 0

摘要

高效的拖拉机路径跟踪方法可以提高作业精度,提高土地利用率,并更有效地为自主拖拉机和精准农业提供服务。本研究设计了一种无模型自适应预测控制-比例积分-派生(MFAPC-PID)方法。在预览理论的基础上,设计了基于航线偏差角的跟踪系统。跟踪系统线性化后,开发了 MFAPC 跟踪系统,并分析了其固有缺陷。参照增量 PID 算法的控制结构,将 MFAPC 视为自适应积分项,通过添加自适应比例项和微分项得到 MFAPC-PID 控制器。为了验证所提出的控制器,进行了协同仿真和硬件在环测试。控制器在不同的路径、路面和拖拉机模型下进行了模拟和测试。与其他方法相比,MFAPC-PID 路径跟踪方法在综合性能、适应性、通用性和鲁棒性方面都表现出了优越性。此外,MFAPC-PID 方法对外界干扰和被控对象模型变化不敏感。
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A model-free adaptive predictive path-tracking controller with PID terms for tractors

An efficient tractor path-tracking method can increase the operational accuracy, improve land utilisation, and more efficiently provide services for autonomous tractors and precision agriculture. In this study, a model-free adaptive predictive control-proportional-integral-derivative (MFAPC-PID) method was devised. Based on preview theory, a tracking system based on course deviation angle was designed. After the tracking system was linearised, an MFAPC tracking system was developed, and its inherent defects were analysed. Referring to the control structure of an incremental PID algorithm, the MFAPC was considered as an adaptive integral item, and the MFAPC-PID controller was obtained by adding adaptive proportional and differential terms. To verify the proposed controller, collaborative simulation and hardware-in-the-loop tests were performed. The controller was simulated and tested under different paths, road surfaces, and tractor models. Compared with other methods, the MFAPC-PID path-tracking method exhibits superior comprehensive performance, adaptability, universality, and robustness. Moreover, the MFAPC-PID method is insensitive to external interference and model changes of controlled objects.

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来源期刊
Biosystems Engineering
Biosystems Engineering 农林科学-农业工程
CiteScore
10.60
自引率
7.80%
发文量
239
审稿时长
53 days
期刊介绍: Biosystems Engineering publishes research in engineering and the physical sciences that represent advances in understanding or modelling of the performance of biological systems for sustainable developments in land use and the environment, agriculture and amenity, bioproduction processes and the food chain. The subject matter of the journal reflects the wide range and interdisciplinary nature of research in engineering for biological systems.
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