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相关概念视频

Block Diagram Reduction01:22

Block Diagram Reduction

157
The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
157
Signal Flow Graphs01:18

Signal Flow Graphs

182
Signal-flow graphs offer a streamlined and intuitive approach to representing control systems, providing an alternative to traditional block diagrams. These graphs use branches to symbolize systems and nodes to represent signals, effectively illustrating the relationships and interactions within the system.
In a signal-flow graph, branches denote the system's transfer functions, while nodes represent the signals. The direction of signal flow is indicated by arrows, with the corresponding...
182
SFG Algebra01:16

SFG Algebra

107
In Signal Flow Graph (SFG) algebra, the value a node represents is determined by the sum of all signals entering that node. This summed value is then transmitted through every branch leaving the node, making the SFG a powerful tool for visualizing and analyzing control systems.
Each node in an SFG corresponds to a variable, and the interactions between nodes are represented by branches with associated gains. When multiple branches lead into a node, the value at that node is the sum of the...
107
Control Systems01:10

Control Systems

1.1K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
1.1K
Control Systems: Applications01:25

Control Systems: Applications

574
Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...
574
Modeling and Similitude01:12

Modeling and Similitude

245
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
245

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相关实验视频

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A Rapid Method for Modeling a Variable Cycle Engine
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自动生成过程模拟场景从声明性控制流变化.

Daniel Barón-Espitia1, Marlon Dumas2, Oscar González-Rojas1

  • 1Systems and Computing Engineering Department, Universidad de los Andes, Bogotá, Colombia.

PeerJ. Computer science
|December 13, 2024
PubMed
概括

本研究引入了一种新的业务流程模拟方法,简化了"如果"情景分析. 它使用生成型深度学习自动创建精确的模拟模型,具有指定的控制流变化,克服复杂性问题.

科学领域:

  • 业务流程管理 业务流程管理
  • 模拟建模模的模拟模型.
  • 人工智能的人工智能

背景情况:

  • 业务流程模拟估计了变化对时间和成本的影响.
  • 数据驱动模拟 (DDS) 从事件日志中发现过程模型,但可以创建复杂的模型.
  • 模型的复杂性阻碍了对"假如"情景的手动调整,特别是控制流变化.

研究的目的:

  • 在业务流程模拟中提出声明式规范和自动生成"假如"场景的方法.
  • 为了解决DDS方法在创建可调节的模拟模型时的复杂性限制.

主要方法:

  • 使用生成型深度学习模型生成事件日志痕迹,反映用户指定的控制流变化.
  • 从这些痕迹中生成一个随机过程模型.
  • 构建基于随机过程模型的"what-if"分析的修改模拟模型.

主要成果:

  • 拟议的方法自动生成"假如"模拟模型,使用用户定义的控制流修改.
  • 生成的模型保持准确度与手动调整的模型相提并论.
  • 成功克服了用于场景分析的DDS中的复杂性障碍.

结论:

关键词:
控制流变化改变了控制流.数据驱动的模拟.声明性规范的声明性规范.随机过程模型的模型.如果分析分析怎么样?

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  • 该方法通过简化复杂的DDS模型的修改来实现高效和准确的"假如"分析.
  • 声明式控制流规范与生成式深度学习相结合,为业务流程模拟提供了强大的解决方案.
  • 便于更容易地探索过程变化及其潜在影响.