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使用具有静态补偿的合作空间操纵器进行灵活的有效载荷运输
Mingyan Xie1, Ti Chen1, Shihao Ni1
1State Key Laboratory of Mechanics and Control for Aerospace Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
ISA transactions
|December 12, 2024
概括
这项研究介绍了一种新的神经网络控制器,用于两个处理灵活有效载荷的空间操纵器. 控制器确保稳定的运输和有效载荷和操纵器的准确定位.
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
- 航空航天工程 航空航天工程
背景情况:
- 太空探索任务通常涉及复杂的机器人系统来操纵有效载荷.
- 使用多个操纵器控制灵活的有效载荷带来了重大的动态挑战.
- 准确的建模和强大的控制对于成功的太空作业至关重要.
研究的目的:
- 为运输灵活有效载荷的两个空间操纵器制定合作控制策略.
- 解决空间操纵任务固有的动态复杂性和不确定性.
- 提高空间机器人系统在有效载荷处理过程中的稳定性和精度.
主要方法:
- 使用假设模式方法对灵活的有效载荷进行分离.
- 基于拉格朗日方程和拉格朗日乘法的系统动态模型的开发.
- 使用静态分析估计有效载荷边界力和扭矩.
- 实现一个辐射基函数神经网络 (RBF NN),用于近似未知系统项.
- 基于NN的合作控制器的设计,包括静态补偿.
- 使用利亚普诺夫理论进行稳定性分析.
主要成果:
- 成功建立了双操纵器,灵活有效载荷系统的动态模型.
- 设计和验证了一种基于NN的,具有静态补偿的新型合作控制器.
- 控制器在驱动操纵器和有效载荷到所需状态时表现出有效性.
- 数字模拟和实验结果证实了控制器的效率和稳定性.
结论:
- 拟议的基于NN的合作控制策略对于处理灵活有效载荷的空间操纵器是有效的.
- 整合静态补偿和RBF NNs可以提高控制性能和系统稳定性.
- 这项研究为太空机器人中精确和稳定的有效载荷运输提供了可行的解决方案.
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