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微型温室嵌入式控制系统的神经控制器实现.

Vasyl Teslyuk1, Ivan Tsmots1, Natalia Kryvinska2

  • 1Department of Automated Control Systems, Lviv Polytechnic National University, Lviv, Ukraine.

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概括
此摘要是机器生成的。

本研究介绍了嵌入式系统的模块化神经控制器,利用人工神经网络进行高效的控制. 基于STM32微控制器的硬件为智能控制应用提供了具有成本效益的解决方案.

关键词:
人工神经网络的人工神经网络控制系统 控制系统 控制系统这是一个智能迷你温室.神经控制器的神经控制器这是STM32的标准.

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科学领域:

  • 控制系统工程 控制系统工程
  • 人工智能的人工智能
  • 嵌入式系统 嵌入式系统

背景情况:

  • 传统的控制系统在嵌入式应用中面临着局限性.
  • 神经网络提供了先进的控制能力,但也带来了实施挑战.
  • 现有的解决方案往往缺乏模块化和成本效益.

研究的目的:

  • 为嵌入式系统提出一种新的神经控制器.
  • 为快速发展设计一个模块化神经控制器结构.
  • 通过使用STM32微控制器来证明成本效益高的实现.

主要方法:

  • 开发一个模块化的神经控制器架构.
  • 使用人工神经网络设计一个运行算法和数据处理模型.
  • 使用STM32微控制器,传感器和执行器的硬件实现.

主要成果:

  • 一个功能性神经控制器,可以处理技术数据.
  • 一个模块化设计,在开发过程中促进系统的改进.
  • 一个低成本的硬件实现,适合嵌入式应用程序.

结论:

  • 拟议的神经控制器有效地将人工神经网络集成到嵌入式控制系统中.
  • 模块化设计和基于软件的神经网络实现允许快速适应和改进.
  • 基于STM32的系统为智能控制提供了实用和经济的解决方案,以迷你温室应用为例.