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相关概念视频

Feedback control systems01:26

Feedback control systems

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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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Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

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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...
79
Load-frequency control01:28

Load-frequency control

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Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
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PD Controller: Design01:26

PD Controller: Design

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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,...
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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.
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Controller configurations are crucial in a car's cruise control system because they manage speed over time to maintain a consistent pace regardless of road conditions, thereby meeting design goals. In traditional control systems, fixed-configuration design involves predetermined controller placement. System performance modifications are known as compensation.
Control-system compensation involves various configurations, most commonly series or cascade compensation, in which the controller...
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适应性通用类型-2模糊模型控制基于非线性网络系统的数据包丢失.

Tarek R Khalifa1, Xian Yu2, Xiaopin Zhong3

  • 1College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, 518060, Guangdong, China; College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, Guangdong, China; Department of Industrial Electronics and Control Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Menoufia, Egypt.

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|February 22, 2025
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概括

本研究介绍了针对面临数据包丢失的网络控制系统 (NCS) 的基于模糊模型的适应性通用类型-2控制 (AGT2-FMBC). 这种新的方法确保了系统稳定性和最佳的跟踪性能,尽管存在通信不确定性.

关键词:
适应性控制是适应性的控制.基于模糊模型的控制控制.一般类型-2模糊系统网络控制系统的网络控制系统.软件包丢弃的情况

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科学领域:

  • 控制系统工程 控制系统工程
  • 模糊逻辑系统 模糊逻辑系统
  • 网络控制系统 (NCS) 是指网络控制系统.

背景情况:

  • 网络控制系统 (NCS) 容易因通信通道中的数据包丢失而导致性能下降.
  • 模拟NCS中的不确定性和非线性对于有效控制至关重要.
  • 现有的控制方法在间歇性通信下经常难以保持稳定性和性能.

研究的目的:

  • 为具有数据包丢失的NCS提出一种基于模糊模型的新型适应性通用类型-2控制 (AGT2-FMBC).
  • 设计一种通用类型-2模糊模型 (GT2FM),用于在线表示具有不确定性的非线性系统.
  • 开发一个自适应控制算法,确保稳定性和最佳跟踪性能.

主要方法:

  • 设计了一个通用类型-2模糊模型 (GT2FM),具有通用类型-2模糊集和Takagi-Sugeno后果.
  • 使用伯努利分布建模了数据包丢失,并实施了缓冲器以减轻其影响.
  • 一个通用型-2模糊控制器 (GT2FC) 是使用并行分布补偿和直接模糊化方法开发的.
  • 新的自适应在线定律是使用Lyapunov稳定定理得出的.

主要成果:

  • 拟议的AGT2-FMBC有效地处理NCS中的数据包丢失.
  • GT2FM准确地表示具有在线不确定性的非线性系统.
  • 适应性控制法确保了趋同和稳定.
  • 控制器在三个非线性NCS的模拟中表现出稳健性.

结论:

  • AGT2-FMBC为控制带有数据包丢失的非线性NCS提供了强大而有效的解决方案.
  • 控制器的自适应性允许在线参数调整,提高性能.
  • 该研究通过对基准非线性系统进行严格的测试来验证拟议方法的有效性.