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相关概念视频

Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

781
A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...
781
Feedback control systems01:26

Feedback control systems

663
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...
663
Relative Motion Analysis - Velocity01:24

Relative Motion Analysis - Velocity

672
A stroke engine has a slider-crank mechanism that converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider.
When an external force is exerted, it sets the crank into a rotational movement. This, in turn, instigates the motion of the connecting rod, leading to what is referred to as a general plane motion. This process involves two key points - point A on the connecting rod...
672
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

508
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...
508
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

683
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...
683
Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

730
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...
730

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Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
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针对USV的事件触发的自适应跟踪控制基于增强的优化后退技术.

Hugan Zhang1, Xianku Zhang2, Yongjin Liu2

  • 1Merchant Marine College, Shanghai Maritime University, Shanghai, 201306, China.

ISA transactions
|December 7, 2025
PubMed
概括

本研究引入了无人地面车辆的自适应控制方法,减少通信负载并改善干扰排斥. 这种新的方法提高了轨迹跟踪性能和系统对环境因素的稳定性.

关键词:
增强优化的后退步骤.事件触发机制事件触发机制固定时间干扰观察员.在USV轨迹跟踪跟踪.

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科学领域:

  • 机器人和控制系统 机器人和控制系统
  • 海洋工程 海洋工程
  • 人工智能的人工智能

背景情况:

  • 无人驾驶地面车辆 (USV) 在轨迹跟踪方面面临挑战,原因是环境干扰,通信限制和复杂的控制设计.
  • 现有的控制方法往往难以实时适应动态的海洋条件和高效的数据处理.

研究的目的:

  • 开发一种针对USV的增强适应性最佳后退控制方法.
  • 为了解决干扰排斥,传感器通信负担和控制器复杂性的局限性.

主要方法:

  • 为了最佳的控制决策和绩效评估,采用了关键行为体强化学习框架.
  • 神经网络被用来估计成本函数梯度,简化了计算.
  • 实施了一个事件触发机制,以减少传感器通信频率.
  • 开发了一个干扰观察器,用于实时估计和补偿环境干扰.

主要成果:

  • 拟议的方法显著降低传感器通信频率.
  • 环境干扰的实时补偿提高了系统的稳定性.
  • 理论分析证实了控制算法的稳定性和有效性.
  • 与传统方法相比,模拟结果显示出更高的性能.

结论:

  • 增强的适应性最佳后退控制方法为USV轨迹跟踪提供了强大的和高效的解决方案.
  • 事件触发机制和干扰观察器的集成在实际USV应用中提供了显著的优势.
  • 该研究验证了在复杂的海洋控制场景中关键行为体强化学习的有效性.