基于扩张状态观测器的管桩自动焊接机滑模控制

doi:10.16180/j.cnki.issn1007-7820.2023.06.001

摘要/Abstract

摘要：

针对管桩自动焊接机中齿轮传动结构带来的齿隙非线性问题,文中提出一种基于扩张状态观测器的改进滑模控制器设计方法。将非线性、时变齿隙模型等价为全局线性化模型,并证明建模误差上限有界。基于该模型,考虑到输入齿隙未知以及外界干扰未知的情况,文中分别设计了滑模控制器和基于扩张状态观测器的改进滑模控制器。前者能够渐进稳定的跟踪输入信号,抗干扰能力强,但存在较大抖振;后者利用扩张状态观测器观测出未知扰动并直接补偿给控制器,在保证跟踪误差在期望精度范围的同时减少了抖振,便于工程实现。仿真实验证明了相较于传统滑模控制器,基于扩张状态观测器的改进滑模控制器系统到达滑模面的速度更快、抖振更少。

关键词: 自动控制技术, 管桩自动焊接机, 输入齿隙, 齿隙线性化, 非线性系统, 鲁棒控制, 滑模控制, 扩张状态观测器

Abstract:

In view of the nonlinear problem of backlash caused by the gear transmission structure in the automatic pipe pile welding machine, an improved sliding mode controller design method based on the extended state observer is proposed. Firstly, the nonlinear and time-varying backlash model is equivalent to a global linearization model, and it is proved that the upper limit of the modeling error is bounded. For the situation with nonlinear input backlash and unknown external disturbance, a sliding mode controller and an improved sliding mode controller based on extended state observer are designed, respectively. The former can track the input signal asymptotically and stably, and has strong anti-interference ability, but it has large chattering. The latter uses the extended state observer to detect the unknown disturbance and directly compensates to the controller, which not only ensures the tracking error within the expected accuracy range, but also reduces chattering. The simulation results show that compared with the traditional sliding mode controller, the improved sliding mode controller system based on the extended state observer reaches the sliding mode surface faster and chatters less.

Key words: automatic control technology, welding robot, input backlash, backlash linearization, nonlinear system, robust control, sliding mode control, extended state observer

中图分类号:

TP242

刘文景,章国宝,刘宇恒. 基于扩张状态观测器的管桩自动焊接机滑模控制[J]. 电子科技, 2023, 36(6): 1-7.

LIU Wenjing,ZHANG Guobao,LIU Yuheng. Sliding Mode Control of Pipe Welding Robot Based on Extended State Observer[J]. Electronic Science and Technology, 2023, 36(6): 1-7.

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SMC		改进SMC+ESO
c	k	ε	k	α	β
20	50	100	50	3.5	0.8

SMC		改进SMC+ESO
c	k	ε	k	α	β
20	200	100	200	3.5	0.8

SMC		改进SMC+ESO
c	k	ε	k	α	β
20	50	100	50	3.5	0.8