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相关概念视频

Root-Locus Method01:19

Root-Locus Method

146
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...
146
PD Controller: Design01:26

PD Controller: Design

219
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,...
219
Controller Configurations01:22

Controller Configurations

94
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...
94
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
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...
106
Feedback control systems01:26

Feedback control systems

305
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...
305
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

95
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...
95

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WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control
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强大的无模型自适应代学习控制用于自动公交车轨迹跟踪系统.

Shida Liu1, Wei Huang1, Honghai Ji1

  • 1The School of Electrical and Control Engineering, The North China University of Technology, Beijing, China.

Science progress
|May 24, 2024
PubMed
概括

一个新的强大的无模型自适应代学习控制 (R-MFAILC) 算法有效地控制横向自动驾驶公共汽车. 这种数据驱动的方法确保了稳定性,并处理通过模拟验证的系统干扰.

科学领域:

  • 控制工程 控制工程 控制工程
  • 机器人技术 机器人技术 机器人技术
  • 人工智能的人工智能

背景情况:

  • 自动驾驶公共汽车需要精确的横向控制才能安全运行.
  • 现有的控制方法可能会因为系统的非线性和数据限制而扎.

研究的目的:

  • 开发一个强大的无模型自适应代学习控制 (R-MFAILC) 算法,用于自主总线横向控制.
  • 为了应对处理非线性测量干扰的挑战,并仅使用输入-输出数据.

主要方法:

  • 在代领域的一个新型动态线性化方法来建模总线系统.
  • 开发一个具有伪梯度 (PG) 的时间变化的数据模型.
  • R-MFAILC控制器的设计包括一个自适应减弱因子.

主要成果:

  • 在R-MFAILC控制器有效地利用只有系统的输入和输出数据.
  • 对非线性测量干扰表现出强大的稳定性.
  • 通过在卡车模拟平台上的模拟来验证有效性.

结论:

  • 拟议的R-MFAILC算法为自主总线横向控制提供了一个稳定和融合的解决方案.
关键词:
自动驾驶的公共汽车侧向运动控制器对非线性干扰的测量.强大的无模型的自适应型代学习控制.

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  • 无模型,数据驱动的方法简化了实施,提高了稳定性.