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相关概念视频

PD Controller: Design01:26

PD Controller: Design

282
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,...
282
Root-Locus Method01:19

Root-Locus Method

180
A cruise control system in a car is designed to maintain a specified speed automatically by adjusting the gas pedal. The system continuously measures the vehicle's speed and makes fine adjustments to the pedal to achieve this goal. The root locus method is particularly useful for understanding how the cruise control system's behavior changes under varying conditions, such as when the car goes uphill, downhill, or faces strong wind resistance.
This system can be represented by a block...
180
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

421
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
421
Controller Configurations01:22

Controller Configurations

119
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...
119
PI Controller: Design01:24

PI Controller: Design

331
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...
331
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

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Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
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Updated: Jul 19, 2025

Operation of the Collaborative Composite Manufacturing CCM System
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模型预测控制器方法用于自动化车辆的路径跟踪.

Ádám Domina1, Viktor Tihanyi1

  • 1Department of Automotive Technologies, Budapest University of Technology and Economics, 1111 Budapest, Hungary.

Sensors (Basel, Switzerland)
|August 12, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种用于自动驾驶汽车的预测控制 (MPC) 模型,提高了路径跟踪精度. 在模型中包括转向动力学,在模拟和现实世界测试中显著改善了控制器性能.

关键词:
在LPV控制中,控制LPV.自动化车辆自动化车辆模型预测控制模型预测控制路径跟踪跟踪路径跟踪方向盘动力学方向盘动力学车辆建模 车辆建模

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科学领域:

  • 汽车工程 汽车工程
  • 控制系统 控制系统
  • 机器人技术 机器人技术 机器人技术

背景情况:

  • 汽车自动化方向盘需要精确的路径跟踪,以确保安全和效率.
  • 现有的控制方法往往简化了车辆动态,可能会限制性能.
  • 模型预测控制 (MPC) 为复杂的轨迹跟踪提供了一个有希望的框架.

研究的目的:

  • 开发和评估一个模型预测控制 (MPC) 战略,用于自动化车辆转向路径跟踪.
  • 调查不同方向盘动态模型 (一级与二级滞后) 对控制性能的影响.
  • 在车辆的自我坐标系统中引入一种用于生成参考轨迹的新方法.

主要方法:

  • 开发了一种包含转向动态的线性参数变化 (LPV) 车辆工厂模型.
  • 实施了级联MPC结构,将转向动力学分为第二个MPC.
  • 拟议的MPC方法和参考轨迹生成通过模拟和测试车辆进行了验证.

主要成果:

  • 第一阶段的方向盘模型显示出比第二阶段的方向盘模型稍微更准确的路径跟踪.
  • 在预测模型中包括转向动态,显著提高了控制器性能.
  • 模拟和实验结果都证实了新型参考定义方法的有效性.

结论:

  • 拟议的MPC方法有效地控制了自动驾驶汽车的方向盘,以准确跟踪路径.
  • 包含详细的方向盘动态模型对于实现控制器高性能至关重要.
  • 新的参考轨迹生成方法在实际应用中被证明是有效的.