模拟 PID 控制的 3DOF 机器人操纵器,使用 Lyapunov 函数来增强轨迹跟踪和利用黄金子算法的稳定性
Muhammad I Azeez1, Khaled R Atia1
1Mechanical Design and Production Engineering Department, Zagazig University, Zagazig 44519, Egypt.
ISA transactions
|December 1, 2023
概括
这项研究使用金优化 (GJO) 算法优化了一个机器人操纵器控制器. GJO算法提高了工业采购任务的跟踪和稳定性.
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
- 计算智能是一种计算智能.
背景情况:
- 机器人操纵器需要精确的控制工业应用.
- 优化比例积分导数 (PID) 控制器对于提高性能至关重要.
- 超启发式算法为复杂的优化问题提供了先进的解决方案.
研究的目的:
- 为了优化一个比例整合导数 (PID) 控制器为一个3-DOF刚性链路机器人操纵器 (RLM).
- 使用金优化 (GJO) 算法来提高跟踪性能和对不确定性的稳定性.
- 为了验证GJO算法的有效性与其他最先进的元启发式技术相比.
主要方法:
- 使用Simscape和Lagrange方法模拟一个3-DOF RLM.
- 使用新的黄金子优化 (GJO) 算法优化PID控制器.
- 使用Lyapunov稳定函数作为控制器调整的目标函数.
主要成果:
- 与PSO,ABC,JSO,WOA,AOA和SCA相比,GJO算法在最小化目标函数方面表现出卓越的性能.
- 优化的PID控制器实现了增强的跟踪性能和稳定性.
- 该系统在Pick and Place (PNP) 任务中显示出对干扰,噪音和有效载荷变化的显著稳定性.
结论:
- 黄金子优化 (GJO) 算法是机器人系统中调整PID控制器的有效方法.
- 优化的控制器显著提高了工业任务的机器人操纵器的性能和稳定性.
- 这种方法为先进的机器人控制策略提供了坚实的基础.
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