基于MIMO超局部模型的自适应增强型无模型控制,使用对合机械电子系统的极端寻找
Dingxin He1, Haoping Wang1, Yang Tian1
1School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, China.
ISA transactions
|December 6, 2024
概括
这项研究引入了多输入多输出 (MIMO) 系统的新型无模型控制,增强了机器人手臂轨迹跟踪. 极端寻找优化控制,在复杂的机械电子系统中提供强大的性能.
科学领域:
- 机械电子和控制系统工程 机械电子和控制系统工程
- 机器人和自动化机器人与自动化
背景情况:
- 机械系统 (例如机器人手臂) 是至关重要的,但由于合和不确定性,很难建模.
- 传统的基于模型的控制对于这些复杂的系统来说往往是不切实际的.
研究的目的:
- 为多输入多输出 (MIMO) 机械系统开发一种可适应的,增强的无模型控制.
- 为了在存在系统不确定性和干扰的情况下实现可靠的轨迹跟踪.
主要方法:
- 开发了一种具有非对角增益矩阵 (α) 的新型MIMO超局部模型,以近似计算系统动态.
- 使用极端寻找 (ES) 技术来优化增益矩阵α.
- 时间延迟估计 (TDE) 和比例导数 (PD) 控制与准确性补偿确保了闭环稳定性.
主要成果:
- 拟议的无模型控制框架有效地处理MIMO机械电子系统.
- 对非对角增强矩阵的极端寻求优化显著提高了控制性能.
- 在机器人操纵器上的模拟表明了该方法的有效性和优越性.
结论:
- 开发的MIMO超局部模型和基于ES的自适应控制为复杂机械电子系统的轨迹跟踪提供了强大的解决方案.
- 该方法提供了通过严格的模拟验证的稳定和高性能控制策略.
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