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Sequence Networks of Rotating Machines

Sequence Networks of Rotating Machines

A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...

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Updated: Jul 16, 2025

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

环吸引器生物灵感的神经网络用于社交机器人导航.

Jesús D Rivero-Ortega¹, Juan S Mosquera-Maturana¹, Josh Pardo-Cabrera¹

¹Department of Engineering, Universidad Autónoma de Occidente, Cali, Colombia.

Frontiers in neurorobotics

|September 18, 2023

概括

这项研究介绍了一种生物灵感的机器人导航系统,使用环吸引神经网络来安全地引导社会代理人. 这种新的方法通过在避开障碍和社会舒适方面超越现有方法来增强人机交互.

关键词:

生物启发的导航系统在决策过程中做出决定.发动机控制器发动机控制器避免障碍避免障碍避免障碍环吸引器网络是一个环吸引器网络.机器人指导机器人指导机器人指导社交导航是社会导航.

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Designing and Implementing Nervous System Simulations on LEGO Robots

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科学领域:

机器人技术机器人技术机器人技术
神经科学是一个神经科学.
人工智能的人工智能

背景情况:

在拥挤的环境中机器人导航在安全和社会互动方面带来了挑战.
像社会力量模型这样的现有方法在处理动态障碍和社会线索方面存在局限性.

研究的目的:

引入一个生物灵感导航系统,用于引导社会代理人的机器人.
在复杂的环境中提高人机交互的安全性和舒适性.

主要方法:

一个生物灵感导航系统,利用环吸引器神经网络进行感知,规划和控制.
模拟实验在一个虚拟的行人区域与静态和动态障碍物.
与社会力量模型进行比较,并使用社会个体指数和相对运动指数快速探索随机树星.

主要成果:

拟议的导航系统有效地指导社会代理人,同时避免障碍.
该系统的表现优于基于评估指标的社会力量模型.
具体指数的整合改善了避免碰撞和社会舒适度.

结论:

生物启发的导航系统为更安全,更舒适的人机交互提供了一个有希望的方法.
环吸引器神经网络为集成导航控制提供了一个强大的框架.
开发的指标在评估社交导航系统方面是有效的.