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相关概念视频

Feedback control systems01:26

Feedback control systems

316
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...
316
Open and closed-loop control systems01:17

Open and closed-loop control systems

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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...
759
Control Systems01:10

Control Systems

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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...
1.2K
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

119
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
119
PD Controller: Design01:26

PD Controller: Design

241
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
241
PI Controller: Design01:24

PI Controller: Design

285
Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
285

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相关实验视频

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Interactive and Visualized Online Experimentation System for Engineering Education and Research
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为非线性批处理过程设计强大的模糊代学习控制.

Wei Zou1, Yanxia Shen1, Lei Wang2

  • 1Engineering Research Center of Internet of Things Technology Applications, Ministry of Education, Jiangnan University, Wuxi 214122, China.

Mathematical biosciences and engineering : MBE
|December 5, 2023
PubMed
概括

一个新的复合模糊代学习控制 (ILC) 方案使用2D模糊模型稳定非线性批处理过程. 这种强大的控制方法确保了通过模拟验证的稳定性和性能.

科学领域:

  • 控制工程 控制工程 控制工程
  • 模糊系统 (Fuzzy Systems) 是一个模糊系统.
  • 非线性系统是非线性系统.

背景情况:

  • 非线性批处理过程由于其复杂的动态和干扰而存在控制挑战.
  • 代学习控制 (ILC) 对于重复的任务是有效的,但需要适应非线性系统.
  • 模糊系统为建模和控制非线性不确定性提供了强大的框架.

研究的目的:

  • 为非线性批处理提出一个二维 (2D) 复合模糊代学习控制 (ILC) 方案.
  • 为了解决非重复性干扰,并确保强大的非对称稳定性和2D $H_\infty$性能.
  • 开发基于线性矩阵不等式 (LMIs) 的控制器设计方法.

主要方法:

  • 通过局部部门非线性方法,使用2D不确定的Takagi-Sugeno (T-S) 模糊模型表示非线性批处理过程.
  • 在开发的模糊模型下,将反控制与ILC方案集成.
  • 使用利亚普诺夫函数和矩阵转换,建立足够的稳定性和性能条件.

主要成果:

  • 获得了足够的条件,以实现强大的非对称稳定性和闭环模糊系统的2D $H_\infty$性能.
  • 通过解决一组线性矩阵不等式 (LMIs) 来获得控制器收益.
关键词:
2D $ H_\infty $ 的表现性能.模糊的代学习控制控制.非线性批量工艺 不线性批量工艺强大的非对称稳定性.不确定的TS模糊模型.

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  • 在三系统和连续式反应堆 (CSTR) 上的模拟证明了该方法的可行性和效率.
  • 结论:

    • 拟议的2D复合模糊ILC方案有效控制非线性批处理过程与非重复性干扰.
    • 该方法保证了强大的稳定性,并实现了所需的性能水平.
    • 基于LMI的设计为控制器合成提供了一个实用的方法.