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相关概念视频

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

132
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
132
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

107
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
107
Classification of Systems-I01:26

Classification of Systems-I

221
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
221
State Space Representation01:27

State Space Representation

245
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
245
Open and closed-loop control systems01:17

Open and closed-loop control systems

826
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
826
Feedback control systems01:26

Feedback control systems

352
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...
352

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一个数据驱动的框架来学习混合动力系统.

Yang Li1, Shengyuan Xu1, Jinqiao Duan2

  • 1School of Automation, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China.

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|June 22, 2023
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概括
此摘要是机器生成的。

本研究引入了一种新的数据驱动方法,用于从时间序列数据中发现混合动态系统,而不需要先前的系统知识. 该框架有效地学习复杂系统的规律,提供广泛的适用性.

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科学领域:

  • 动态系统理论 动态系统理论
  • 机器学习 机器学习
  • 数据科学数据科学数据科学

背景情况:

  • 混合动力系统的现有数据驱动方法通常需要对模型结构的先验知识.
  • 参数识别通常仅限于预定义的函数或规定的形式.

研究的目的:

  • 开发一种新的数据驱动框架,直接从时间序列数据中发现混合动力系统.
  • 消除对系统底层结构或功能事先知识的需求.

主要方法:

  • 采用双循环算法来隔离属于单个子系统的数据.
  • 剩余网络被代训练以接近子系统动态.
  • 一个完全连接的神经网络估计子系统之间的过渡规则.

主要成果:

  • 提出的方法成功地识别了跨各种维度和结构的混合动力系统.
  • 在几个原型实例上证明了有效性和准确性.
  • 该框架从数据中学习进化规律.

结论:

  • 这种新的框架为学习混合动力系统提供了有效的工具,不需要先前的知识.
  • 该方法显示了从可用的数据集分析复杂系统的广泛适用性.