基于改进的CPG的气动软生物机器人的控制策略研究
Wenchuan Zhao1, Yu Zhang2, Kian Meng Lim3
1School of Information Science and Engineering, Shenyang University of Technology, Shenyang, China.
PloS one
|July 5, 2024
概括
本研究介绍了一种新的中央模式生成器 (CPG) -ANFIS-PID控制策略,用于气动软机器人. 这种方法提高了运动控制精度和防干扰能力,使机器人运动具有适应性和精确性.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统 控制系统
- 生物模拟学是一种生物模拟学.
背景情况:
- 软机器人在机动性和适应性方面提供了独特的优势.
- 有效的运动控制对于气动软机器人的实际应用至关重要.
- 现有的控制策略往往在复杂环境中难以准确和防干扰.
研究的目的:
- 为气动软生物机器人提出一个改进的基于中央模式生成器 (CPG) 的运动控制策略.
- 为了提高软机器人运动控制的准确性和防干扰能力.
- 开发一种适用于气动软机器人的节奏运动控制方法.
主要方法:
- 使用22个合的霍普菲尔德神经元非线性振荡器构建了一个双层神经网络拓模型.
- 开发了一个CPG-ANFIS-PID (中央模式生成器-自适应神经模糊推理系统-比例-整体-导数) 运动控制策略.
- 利用基于ANFIS的离线学习和会员功能培训来构建控制策略.
主要成果:
- 在CPG-ANFIS-PID策略中,在不同游泳模式中对输入参数变化做出了快速响应.
- 控制策略稳定地输出了光滑,连续的动态位置信号.
- 机器人原型的实验分析证实了稳定的合波形信号输出和生物节奏运动推进.
结论:
- 拟议的CPG-ANFIS-PID控制策略为气动软生物机器人提供了显著的准确性和防干扰特性.
- 该战略使机器人能够表现出机动性,灵活性和环境适应性.
- 这项工作为气动软生物机器人建立了可行的控制策略和节奏运动控制方法.
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