基于单层神经网络的农业移动机器人控制

C. Gökçe
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引用次数: 0

摘要

在这项研究中,我们提出了一种新的控制器架构和设计,用于农场和温室中使用的农业移动机器人的自动控制。这项研究有两个新奇之处。第一个新颖之处是提出了一种全新类型的控制器架构,其中参考输入和测量输出分别独立地馈送到控制器。目前在文献中使用的控制器架构仅使用参考和测量之间的差异,即误差信号。本研究中提出的架构是完全新颖的,因为不仅在控制器中使用误差信息,而且参考输入中的信息和测量输出中的信息是分开使用的。这意味着一种全新的外观控制系统,通过最大限度地利用信息来实现卓越的性能。这种性能提升在论文中显示,与最先进的控制器相比,所提出的架构实现了高达2000%的性能提升。其次,控制器结构由最初简单的PID结构发展为复杂的结构。利用最大的信息来设计控制器是以计算复杂度为代价的。从最初简单的PID等效控制器发展控制器的第二个新颖之处通过使问题易于处理和有效计算来解决这一困难。这样,所提出的新型控制器可以在几分钟内在商用笔记本电脑上设计出来。在一个模拟农业移动机器人上对所提出的控制器进行了测试,并与已有的最优控制器进行了比较。人们认为,所提出的架构将在未来的自动控制器中占据主导地位,并使当前最先进的控制器过时。这是因为在控制器设计中充分利用了信息,具有较强的抗扰性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single-layer neural-network based control of agricultural mobile robot
In this study, we propose a novel controller architecture and design for the automatic control of agricultural mobile robots to be used in farms and greenhouses. There are two novelties of this study. The first novelty is a completely new type of controller architecture proposed in which reference inputs and measured outputs are fed separately independent from each other to the controller. The controller architecture currently used in the literature uses only the difference between reference and measurement which is the error signal. The proposed architecture in this study is completely novel in the sense that not only the error information is used in the controller but also the information in reference inputs and information in measured outputs are used separately. This means a completely new type of look to control system by utilizing the information maximally in order to achieve superior performance. This performance boost is shown in the paper where the proposed architecture achieves up to 2000% better performance compared with state-of-the-art controllers. Second, controller architecture is grown to a complex structure from an initially simple PID structure. Using the maximal information comes with the cost of computational complexity to design the controller. The second novelty of growing the controller from initially simple PID equivalent controller tackles this difficulty by making the problem tractable and efficient to compute. This way the proposed novel controller can be designed within minutes in a commercially available laptop computer. The proposed controller is tested on a simulated agricultural mobile robot and results are compared with a previous state-of-the-art optimal controller. It is believed that the proposed architecture will be dominant in future automatic controllers and make current state-of-the-art controllers obsolete. This is because of the full utilization of information in controller design which results in robust disturbance rejection performance.
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