disturbance switching

简明释义

故障切换

英英释义

例句

1.Implementing disturbance switching in our feedback loop improved the overall performance of the automated system.

在我们的反馈回路中实施干扰切换提高了自动化系统的整体性能。

2.The algorithm implemented for the robotic arm includes a feature for disturbance switching to adjust its position when unexpected forces are detected.

该机器人手臂实现的算法包含了一个干扰切换功能，以便在检测到意外力量时调整其位置。

3.The new drone model features disturbance switching technology that allows it to adapt to wind changes during flight.

新型无人机模型采用了干扰切换技术，使其能够在飞行过程中适应风速变化。

4.In control systems, disturbance switching can significantly enhance stability by quickly responding to external disturbances.

在控制系统中，干扰切换可以通过快速响应外部干扰显著提高稳定性。

5.During the experiment, we observed how disturbance switching helped maintain the temperature of the reactor despite fluctuations.

在实验中，我们观察到干扰切换如何帮助保持反应器的温度，尽管存在波动。

作文

In the realm of control systems and robotics, the concept of disturbance switching plays a crucial role in ensuring stability and performance. Essentially, disturbance switching refers to the mechanism by which a system can adapt to unexpected changes or disturbances in its environment. These disturbances can come from various sources, such as external forces acting on a robotic arm or fluctuations in sensor readings. The ability to switch between different modes of operation in response to these disturbances is vital for maintaining the desired output of the system.One of the primary applications of disturbance switching is in autonomous vehicles. As these vehicles navigate through dynamic environments, they must constantly adjust their paths and behaviors based on real-time data. For instance, if a sudden obstacle appears in the vehicle's path, the system must engage disturbance switching to reroute effectively. This involves not only detecting the obstacle but also deciding how to respond—whether to stop, slow down, or change direction entirely. The efficiency of this process directly impacts the safety and reliability of autonomous driving technology.Moreover, disturbance switching is not limited to physical systems; it is also applicable in software systems, particularly in adaptive algorithms. In machine learning, models often encounter unexpected data patterns that can lead to poor predictions. By incorporating disturbance switching techniques, these models can adjust their parameters or even switch to entirely different algorithms when faced with significant deviations from expected inputs. This adaptability enhances the robustness of the model and ensures better performance over time.The theoretical foundation of disturbance switching lies in control theory, where systems are designed to maintain stability despite the presence of disturbances. Engineers often utilize feedback loops to monitor system performance continuously. When a disturbance is detected, the feedback loop triggers a response that may involve switching control strategies or altering system parameters to counteract the effects of the disturbance. This proactive approach is essential for high-stakes applications, such as aerospace engineering, where failure to respond appropriately to disturbances can have catastrophic consequences.Furthermore, the implications of disturbance switching extend beyond technical applications. In everyday life, individuals often encounter disturbances that require them to switch their plans or strategies. For example, a person may have a detailed itinerary for a trip, but unexpected weather conditions could force them to alter their route or activities. This ability to adapt is a form of disturbance switching at a personal level, showcasing the universal nature of this concept.In conclusion, disturbance switching is a vital concept across various fields, from robotics to machine learning and even in our daily lives. Its significance lies in the ability to respond effectively to unexpected changes, thereby maintaining stability and performance. As technology continues to advance, the importance of integrating disturbance switching mechanisms will only grow, making it an essential area of study and application for engineers, scientists, and individuals alike. Understanding and mastering disturbance switching can lead to more resilient systems and better decision-making processes in the face of uncertainty.

在控制系统和机器人领域，干扰切换的概念在确保稳定性和性能方面起着至关重要的作用。基本上，干扰切换是指系统能够适应环境中意外变化或干扰的机制。这些干扰可能来自各种来源，例如施加在机器人臂上的外力或传感器读数的波动。根据这些干扰在不同操作模式之间切换的能力对于保持系统所需输出至关重要。干扰切换的主要应用之一是在自主车辆中。当这些车辆在动态环境中导航时，它们必须根据实时数据不断调整路径和行为。例如，如果车辆路径上突然出现障碍物，系统必须启用干扰切换以有效地重新规划路线。这不仅涉及到检测障碍物，还涉及到决定如何响应——是停止、减速还是完全改变方向。这个过程的效率直接影响到自主驾驶技术的安全性和可靠性。此外，干扰切换不仅限于物理系统；它也适用于软件系统，特别是在自适应算法中。在机器学习中，模型经常会遇到意外的数据模式，这可能导致预测不佳。通过结合干扰切换技术，这些模型可以在面临显著偏离预期输入时调整其参数，甚至切换到完全不同的算法。这种适应性增强了模型的鲁棒性，并确保随着时间的推移获得更好的性能。干扰切换的理论基础源于控制理论，在该理论中，系统被设计为在存在干扰的情况下保持稳定。工程师通常利用反馈回路持续监测系统性能。当检测到干扰时，反馈回路触发一种响应，这可能涉及切换控制策略或改变系统参数，以抵消干扰的影响。这种主动的方式对于高风险应用（如航空航天工程）至关重要，因为未能适当地响应干扰可能会导致灾难性后果。此外，干扰切换的影响超越了技术应用。在日常生活中，个人经常会遇到需要切换计划或策略的干扰。例如，一个人可能有详细的旅行行程，但意外的天气条件可能迫使他们改变路线或活动。这种适应能力是个人层面的干扰切换，展示了这一概念的普遍性。总之，干扰切换是各个领域的重要概念，从机器人技术到机器学习，甚至在我们的日常生活中。它的重要性在于能够有效应对意外变化，从而保持稳定性和性能。随着技术的不断进步，整合干扰切换机制的重要性只会增加，使其成为工程师、科学家和个人都必须研究和应用的关键领域。理解和掌握干扰切换可以导致更具韧性的系统以及在不确定性面前更好的决策过程。