基于SAC最佳参数查找算法的机器人常力研磨控制器
Chosei Rei1, Qichao Wang2, Linlin Chen3
1Nobot Intelligent Equipment (Shandong) Co., Ltd, Liaocheng, Shandong, China.
Scientific reports
|June 19, 2024
概括
本研究介绍了一种软演员-关键 (SAC) 算法,以优化比例-整数-导数 (PID) 控制器用于机器人研磨. 增强的控制器实现稳定的恒定力研磨,尽管环境变化.
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:
- 传统的比例整数导数 (PID) 控制器在动态环境条件下难以保持恒定的力研磨.
- 在机器人应用中,精确调整PID控制器的补偿条款是一个挑战.
- 调整机器人研磨力以适应环境变化需要先进的控制策略.
研究的目的:
- 开发一个最佳的参数查找算法用于PID控制器补偿条款使用软-演员-关键 (SAC).
- 为了使机器人中稳定和自适应的恒定力研磨控制.
- 为了解决PID控制器获得最佳补偿参数的困难.
主要方法:
- 基于软-演员-关键 (SAC) 的最佳参数查找算法被开发出来,结合了状态动作训练,规范化,奖励函数设计和深度神经网络架构.
- 使用SAC算法来确定PID控制器的最佳补偿参数.
- 为了验证算法的性能,创建了一个具有力反的研磨机器人的模拟模型.
主要成果:
- 经过训练的控制器在模拟中展示了实现恒定力研磨的能力.
- 该算法成功地确定了PID控制器的最佳补偿参数.
- 在实体机器人上的实验验证证了拟议的控制策略的有效性和环境适应性.
结论:
- 基于软-演员-关键 (SAC) 的最佳参数查找算法有效地增强了用于恒定力研磨的PID控制器.
- 开发的方法为在不断变化的环境条件下实现稳定的机器人研磨提供了强大的解决方案.
- 这种方法显示出在机器人制造过程中提高精度和适应性的巨大潜力.
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