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相关概念视频

Modeling and Similitude01:12

Modeling and Similitude

165
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
165
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

93
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...
93
Typical Model Studies01:30

Typical Model Studies

211
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
211
Feedback control systems01:26

Feedback control systems

262
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...
262
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...
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Controller Configurations01:22

Controller Configurations

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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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相关实验视频

Updated: May 21, 2025

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility
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使用强化学习和非线性模型预测控制的自主水面船的数字双胞胎同步.

Henrik Stokland Berg1, Daniel Menges1, Trym Tengesdal1

  • 1Department of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway.

Scientific reports
|March 19, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了使用深度强化学习 (DRL) 和非线性模型预测控制 (NMPC) 的自主水面船 (ASV) 的自适应控制. 这提高了ASV的可靠性和在动态的海上环境中数字双胞胎同步.

关键词:
自主水面船 自主水面船 自主水面船 自主水面船深度强化学习的学习.模型识别 模型识别非线性模型预测控制的非线性模型参数优化的参数优化

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科学领域:

  • 海上机器人技术 在海上机器人技术
  • 控制工程 控制工程 控制工程
  • 人工智能的人工智能是人工智能.

背景情况:

  • 目前的自主水面船 (ASV) 控制系统正在与模型不确定性和参数变化作斗争.
  • 这种限制在复杂,动态的海上条件下损害了ASV的可靠性,需要适应性解决方案.

研究的目的:

  • 为ASV控制开发一个集成的深度强化学习 (DRL) 和非线性模型预测控制 (NMPC) 方法.
  • 确保ASV的数字双胞胎与其物理对应之间的持续同步,以提高准确性和适应性.
  • 为了优化ASV控制性能,并实时识别未知的模型参数.

主要方法:

  • 集成DRL以优化NMPC参数和识别未知模型参数.
  • 利用数字双胞胎在模拟海上环境中为控制人员提供无风险的培训.
  • 通过DRL进行实时参数识别和NMPC调.

主要成果:

  • 在改善ASV控制性能方面,DRL-NMPC方法的有效性已被证明.
  • 在动态和不确定的海上条件下提高ASV的可靠性和适应性.
  • 数字双胞胎与物理ASVs的成功同步,通过广泛的模拟进行验证.

结论:

  • 拟议的DRL-NMPC框架显著提高了ASV的安全性,效率和可靠性.
  • 这种方法为动态环境中的ASV控制挑战提供了强大的解决方案.
  • 该研究为先进的自主海上导航和控制系统奠定了基础.