一个无模型的终端滑动模式控制机器人:实现固定时间规定的性能和融合
Thanh Nguyen Truong1, Anh Tuan Vo1, Hee-Jun Kang1
1School of Electrical Engineering, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan, 44610, Republic of Korea.
ISA transactions
|November 17, 2023
概括
这项研究提出了一种基于神经网络的机器人操纵器新的控制策略,提高了机器人的性能和准确性,同时减少了聊天. 这种新方法克服了传统滑动模式控制器的局限性.
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:
- 传统的基于模型的滑动模式 (SM) 控制器面临的挑战包括精确的模型要求,干扰限制知识和聊天.
- 现有的方法在固定时间的融合和机器人操纵器的规定的性能方面扎.
研究的目的:
- 为机器人操纵器开发一个强大而准确的控制策略,克服传统滑动模式控制的局限性.
- 为了提高响应性能,位置跟踪精度,并减少超越和稳定状态错误.
- 消除对精确系统模型和对干扰上限的知识的需求.
主要方法:
- 纳入神经网络 (NN) 以消除对准确系统模型的需求.
- 引入一种新的固定时间规定的性能控制 (PPC),以提高响应和准确性.
- 利用更快的终端滑动模式 (TSM) 表面和具有可适应因子的新型固定时间达到控制算法 (RCA).
主要成果:
- 拟议的战略显著提高了机器人操纵器的融合率和跟踪精度.
- 证明了控制信号喋喋不休的减少和加强控制器的稳定性.
- 通过对3DOF机器人操纵器的模拟来验证有效性和稳定性,使用Lyapunov标准.
结论:
- 新的控制策略有效地解决了机器人操纵器传统滑动模式控制器的局限性.
- 综合方法实现了所需的性能目标,包括提高准确性和减少聊天.
- 该方法为先进的机器人操纵器控制提供了强大而高效的解决方案.
相关概念视频
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01:21Linear Approximation in Time Domain
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01:22Controller Configurations
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01:17Open and closed-loop control systems
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01:26Feedback control systems
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01:19PID Controller
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