适应性性能增强控制用于具有模型不确定性和执行器故障的柔性关节操纵器
Hejia Gao1, Yuanyuan Zhao1, Chuanfeng He1
1School of Artificial Intelligence, Anhui University, Hefei 230601, China; Engineering Research Center of Autonomous Unmanned System Technology, Ministry of Education, Hefei, Anhui, China; Anhui Provincial Key Laboratory of Security Artificial Intelligence, Anhui University, Hefei 230601, China.
ISA transactions
|December 24, 2025
概括
本研究介绍了灵活关节机器人操纵器 (FJRM) 的自适应性性能增强 (APE) 控制方法. 它改善了轨迹跟踪和对不确定性和故障的稳定性,优于现有的方法.
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
- 人工智能的人工智能
背景情况:
- 灵活关节机器人操纵器 (FJRM) 提供高灵活性和精度,但容易发生故障.
- 这些故障会降低操作稳定性,准确性和设备寿命.
- 有效的控制策略对于可靠的FJRM运行至关重要.
研究的目的:
- 为FJRM提出一种新的适应性性能增强 (APE) 控制方法.
- 解决FJRM系统中的模型不确定性和执行器故障.
- 为了提高轨迹跟踪的准确性和系统的稳定性.
主要方法:
- 一个自适应神经网络 (ANN) 算法补偿建模错误.
- 一个非单元终端滑动模式 (NTSM) 策略提供了合规控制.
- 利亚普诺夫的直接方法验证了闭环系统的稳定性.
主要成果:
- APE控制方法证明了不确定的机器人系统的有效轨迹跟踪.
- NTSM控制增强了稳定性和干扰抑制.
- 在Gazebo平台和Baxter机器人上的模拟和实验证实了有效性.
结论:
- 拟议的APE控制方法显著优于FNN,NN和PD控制器.
- APE方法为FJRM提供了优越的控制性能.
- 这项研究有助于使机器人操纵器操作更加稳定和可靠.
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