有效的在线控制器调整为通向移动机器人使用多变量多目标多项式预测模型和进化优化
Alam Gabriel Rojas-López1, Miguel Gabriel Villarreal-Cervantes1, Alejandro Rodríguez-Molina2
1Mechatronics Section, Postgraduate Department, OMD Laboratory, Instituto Politécnico Nacional-Centro de Innovación y Desarrollo Tecnológico en Cómputo, Mexico City 07700, Mexico.
Biomimetics (Basel, Switzerland)
|February 25, 2025
概括
这项研究介绍了一种高效的在线生物灵感控制器调方法,用于使用代理建模的移动机器人. 这种方法可以显著降低计算负载,同时在不确定的条件下保持或提高控制器性能.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统工程 控制系统工程
- 计算智能是一种计算智能.
背景情况:
- 移动机器人在不可预测的环境中工作,需要先进的控制器来进行动态参数调整.
- 在线生物灵感控制器调整为处理不确定性提供了创新的解决方案,但需要大量的计算资源.
研究的目的:
- 开发一种高效的在线生物灵感控制器调方法,用于使用代理建模的全方位移动机器人.
- 为了减少控制器调整的计算负载,而不会影响动态环境中的性能.
主要方法:
- 纳入多项式响应表面方法用于系统识别和行为预测.
- 开发一种在线生物灵感控制器调方法,利用代用模型.
- 对最先进的在线,离线强和离线非强的生物灵感调方法进行比较分析.
主要成果:
- 与现有的在线方法相比,拟议的方法可将计算负载降低高达62.85%.
- 与离线方法相比,控制器的性能在不利条件下保持不变,并提高了高达93%.
- 该方法显示出优越的性能和较低的计算负载,与基于高斯过程回归的替代调整方法相比.
结论:
- 开发的控制器调整方法显著减少了移动机器人控制系统的执行时间.
- 它即使在不利的环境不确定性和干扰下也保持了闭环性能.
- 这代表了这种代理辅助控制器调整策略在通向移动机器人上的首次应用.
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