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相关概念视频

Conservation of Mass in Fixed, Nondeforming Control Volume01:07

Conservation of Mass in Fixed, Nondeforming Control Volume

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The principle of conservation of mass is fundamental in fluid dynamics and is crucial for analyzing flow within fixed control volumes, such as pipes or ducts. This principle states that the total mass within a control volume remains constant unless altered by the inflow or outflow of mass through the control surfaces. This results in a vital relationship for steady, incompressible flow where the mass entering a system equals the mass leaving it.
In the case of a sewer pipe, which can be modeled...
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Conservation of Mass in Finite Cotrol Volume01:16

Conservation of Mass in Finite Cotrol Volume

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The principle of conservation of mass is a fundamental law in fluid mechanics and is applied using the continuity equation. We apply the concept to a finite control volume to derive the continuity equation.
A system is defined as a collection of unchanging contents, and the conservation of mass states that a system's mass is constant.
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Conservation of Mass in Moving, Nondeforming Control Volume01:14

Conservation of Mass in Moving, Nondeforming Control Volume

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Stormwater detention basins are essential in managing runoff during heavy rainfall, particularly in urban areas where impervious surfaces increase the risk of flooding. Understanding the conservation of mass in these systems allows engineers to optimize basin performance, balancing inflow, outflow, and water storage.
In the context of a detention basin, the conservation of mass states that the total mass of water entering the basin must equal the mass leaving the basin plus any accumulation of...
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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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Feedback control systems01:26

Feedback control systems

314
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
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Conservation of Energy in Control Volume01:14

Conservation of Energy in Control Volume

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Consider a turbine operating under steady-flow conditions. The control volume is drawn around the turbine, with fluid entering at one point and exiting at another. The turbine extracts energy from the fluid, which performs mechanical work (shaft work).
For steady flow systems, the time derivative of the stored energy becomes zero since there is no energy accumulation within the control volume. This simplifies the energy equation to:
842

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相关实验视频

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WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
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基于强化学习的共识控制,用于有间歇性约束的MAS.

Ao Luo1, Qi Zhou1, Hongru Ren1

  • 1School of Automation, Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control, Guangdong University of Technology, Guangzhou, 510000, Guangdong, China.

Neural networks : the official journal of the International Neural Network Society
|January 17, 2024
PubMed
概括

本研究提出了一种用于控制具有间歇性约束的多代理系统的新方法. 该方法有效地处理没有可行性条件的限制,确保系统稳定性和最佳性能.

关键词:
复合学习是一种复合学习.间歇性约束 间歇性的约束多代理系统是多代理系统.神经网络的神经网络的神经网络强化学习是一种强化学习.

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A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
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科学领域:

  • 控制理论 控制理论
  • 人工智能的人工智能
  • 系统工程 系统工程

背景情况:

  • 多代理系统 (MAS) 在各种应用中至关重要.
  • 通过严格的反结构和间歇性约束来控制MAS是一项挑战.
  • 现有的方法往往需要可行性条件,或者存在复杂性问题.

研究的目的:

  • 开发一个适应的最佳共识控制策略,用于MAS与间歇性约束.
  • 为了应对没有可行性条件的间歇性约束的挑战.
  • 为了克服复杂性爆炸问题在后退控制.

主要方法:

  • 设计一种新的类似开关的功能和协调转换,以处理间歇性约束.
  • 采用复合学习算法和神经网络用于基于标识符-演员-关键的强化学习策略.
  • 使用非线性动态表面控制 (DSC) 来减轻复杂性.
  • 应用利亚普诺夫稳定理论来证明系统的边界性.

主要成果:

  • 成功将受约束状态转换为不受约束状态,解决间歇性约束问题.
  • 开发了一种基于标识符-演员-关键的简化强化学习方法,用于近似的最佳控制.
  • 消除了后退控制中固有的"复杂性爆炸"问题.
  • 通过利亚普诺夫稳定理论证明了闭环系统中所有信号的局限性.

结论:

  • 提出的方法有效地解决了MAS与间歇性约束的适应性最佳共识控制问题.
  • 这种方法消除了对可行性条件的需求,并简化了控制设计.
  • 模拟示例证实了该方法的实际有效性和稳定性.