一种利用多点匹配的水下机器人控制器的新近方法
Umesh Kumar Yadav1, V P Singh1, Luigi Fortuna2,3
1Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur, 302017, India.
Scientific reports
|August 22, 2025
概括
这项研究使用多点匹配和灰色狼优化将高级水下机器人车辆 (URV) 控制器与低级模型相近. 这为URV系统提供了高效和经济的控制器.
科学领域:
- 机器人技术
- 控制系统工程
- 优化算法
背景情况:
- 水下机器人车辆 (URV) 的性能受到复杂的内部和外部动态的影响.
- 有效的控制对于实现URV所需的动力和运营效率至关重要.
- 将更高级的控制器与更低级的模型相提并论,为更经济,更有效的控制解决方案提供了潜力.
研究的目的:
- 开发一个高效,有效和经济的低级 (LO) 控制器用于高级 (HO) 水下机器人车辆 (URV) 系统.
- 使用多点匹配技术将HO URV控制器与LO URV控制器相近.
- 使用灰狼优化算法 (GWOA) 优化控制器近似值.
主要方法:
- 使用扩展参数,将HO URV控制器与LO URV控制器进行近似.
- 通过多点匹配来最大限度地减少HO和LO控制器扩展参数之间的错误,以目标函数 (OF) 形式表达.
- 使用GWOA优化OF,以稳定状态匹配和Hurwitz稳定性标准为约束.
主要成果:
- 提出的多点匹配方法成功生成了LO URV模型.
- 通过对现有的LO URV模型进行验证,证明了该方法的有效性.
- 性能评估显示了由响应分析和性能错误值 (PEV) 的统计数据支持的衍生LO控制器的适用性.
结论:
- 提出的方法有效地将高阶URV控制器与低阶模型相近.
- 多点匹配和GWOA的整合为URV提供了高效和稳定的控制策略.
- 开发的LO控制器为URV应用提供了实用和经济的解决方案.
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