具有状态约束的机械臂切换自适应控制

万敏; 杨山山

doi:10.13433/j.cnki.1003-8728.20200623

具有状态约束的机械臂切换自适应控制

doi: 10.13433/j.cnki.1003-8728.20200623

万敏,
杨山山

西南石油大学机电工程学院, 成都 610000

基金项目:

国家自然科学基金项目 51875489

详细信息

作者简介:
万敏(1977-), 教授, 博士, 研究方向为智能控制技术和自动化装置, 18940103@qq.com

中图分类号: TP273
计量
- 文章访问数: 103
- HTML全文浏览量: 19
- PDF下载量: 21
- 被引次数: 0
出版历程
- 收稿日期: 2021-05-27
- 刊出日期: 2023-04-25

Adaptive Control of Manipulator Switching with State Constraints

College of Mechanical and Electrical Engineering, Southwest Petroleum University, Chengdu 610000, China

摘要

摘要: 为了解决具有状态约束的机械臂的控制问题, 本文针对一类具有全状态约束和状态不完全可测的切换严格反馈非线性系统进行研究, 通过引入状态观测器、自适应神经网络和动态表面控制技术, 设计了一种基于径向基函数(RBF)神经网络的自适应输出反馈控制方法。利用Lyapunov方法和平均驻留时间理论(ADT)保证了闭环系统所有信号是半全局一致最终有界的(SGUUB), 通过数值例子仿真验证了所提方法的有效性。最后将该方法应用于带电机驱动的机械臂并进行仿真实验, 仿真结果表明, 机械臂轨迹跟踪误差很小, 有着良好的控制精度, 同时也表明所提出的控制算法能够应用于实际工程模型。
- 动态面控制 /
- 全状态约束 /
- 非线性切换系统 /
- 神经网络状态观测器 /
- 机械臂轨迹控制
Abstract: In order to control manipulator switching with state constraints, this paper studies a class of strict-feedback nonlinear switching systems with full state constraints and incompletely measurable states. By introducing state observer, adaptive neural network and dynamic surface control technique, an adaptive output feedback control method based on the radial basis function (RBF) neural network is designed. The Lyapunov method and the average dwell time theory (ADT) are used to ensure that all signals in the closed-loop system are uniformly ultimately bounded. Numerical examples show the effectiveness of the semi-globally proposed method. Finally, the mechanical arm with motor drive is simulated, and the simulation results show that the trajectory tracking error of the manipulator is very small and has good control accuracy and that the proposed control method can be applied to actual engineering models.
- dynamic surface control /
- full state constrains /
- nonlinear switching system /
- neural network state observer /
- manipulator trajectory control

HTML全文

图 1 系统输出y和参考信号y_d的跟踪轨迹

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图 2 跟踪误差z₁

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图 3 系统状态x₁和其状态观测值₁的轨迹

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图 4 系统状态x₂和其状态观测值₂的轨迹

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图 5 切换信号

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图 6 控制器轨迹

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图 7 位置输出信号y和参考信号y_d的跟踪轨迹

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图 8 位置跟踪误差z₁

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图 9 位置输出信号x₁和其状态观测值₁的轨迹

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图 10 速度信号x₂和其状态观测值₂的轨迹

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图 11 电机转矩x₃和其状态观测值₃的轨迹

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图 12 机构臂切换信号

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图 13 机构臂控制器轨迹

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