对于没有速度测量的受约束机器人系统,事件触发的自适应神经规定的性能接入控制
Penghui Fan1, Jinzhu Peng2, Hongshan Yu3
1School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China.
ISA transactions
|August 20, 2024
概括
这项研究介绍了无速度传感器的机器人事件触发的自适应神经规定的性能准入控制 (ETANPPAC). 新的控制方案有效地管理受限制的机器人系统,同时最大限度地减少通信负载.
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:
- 人机交互需要合规的控制策略.
- 控制没有速度传感器的机器人系统带来了重大挑战.
- 现有的方法可能会面临轨迹限制和通信空头的困难.
研究的目的:
- 提出一个事件触发的自适应神经规定的性能入门控制 (ETANPPAC) 方案.
- 为了能够精确控制缺乏速度传感器的受限制机器人系统.
- 提高人机交互的安全性和效率.
主要方法:
- 使用入口关系和和函数重塑所需的轨迹,以确保安全的相互作用.
- 对于规定的性能错误约束,采用一个障碍力普诺夫函数.
- 使用速度观察器和辐射基函数神经网络进行状态估计和不确定性补偿.
- 实施事件触发机制以减少通信负担并避免Zeno行为.
主要成果:
- 在限制条件下,ETANPPAC计划有效地追踪了所需的轨迹.
- 与传统方法相比,拟议的方法显著降低了通信负载.
- 模拟和实验结果验证了控制方案的性能和效率.
结论:
- ETANPPAC方案提供了一个强大的解决方案,用于控制没有速度传感器的受约束机器人系统.
- 事件触发机制提高了机器人控制中的通信效率.
- 这种方法在人机交互场景中提高了安全性和性能.
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