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Design of admittance controller with sliding mode based on disturbance observer for elbow joint actuated by pneumatic muscles
Industrial Robot ( IF 1.8 ) Pub Date : 2020-05-20 , DOI: 10.1108/ir-12-2019-0246
Binrui Wang , Jiqing Huang , Guoyang Shen , Dijian Chen

Purpose

Active compliance control is the key technology for Tri-Co robots (coexisting–cooperative–cognitive robots) to interact with the environment and people. This study aims to make the robot arm shake hands compliantly with people; the paper proposed two closed-loop-compliant control schemes for the dynamic identification of cascade elbow joint.

Design/methodology/approach

The active compliance control strategy consists of inner and outer loops. The inner loop is the position control using sliding mode control with disturbance observer (SMCDO), in which a new saturation function is designed to replace the traditional signal function of sliding mode control (SMC) law so as to mitigate chatter. The outer loop is the admittance control to regulate the dynamic behaviours of the elbow joint, i.e. its impedance. The simulation is carried out to verify the performance of the proposed control scheme.

Findings

The results show that the chatter of traditional SMC can be effectively eliminated by using SMCDO with this saturation function. In addition, for the handshake task, the value of threshold force and elbow joint compliance is defined. Then, the threshold force tests, impact tests and elbow-joint compliance tests are carried out. The results show that, in the impedance model, the elbow joint compliance only depends on the stiffness parameters, not on the position control loop.

Practical implications

The effectiveness of the admittance control based on SMCDO can improve the adaptability of industrial manipulator in different working environments to some degree.

Originality/value

The admittance control with SMCDO completed trajectory tracking has higher accuracy than that based on SMC.



中文翻译:

基于扰动观测器的气动肌肉肘关节滑模导纳控制器设计

目的

主动合规性控制是Tri-Co机器人(共存,合作,认知机器人)与环境和人互动的关键技术。这项研究旨在使机器人手臂与人握手。提出了两种闭环顺应性控制方案,用于级联肘关节的动态辨识。

设计/方法/方法

主动合规控制策略由内部和外部循环组成。内环是使用带有扰动观测器的滑模控制(SMCDO)的位置控制,其中设计了新的饱和函数来代替滑模控制(SMC)法则的传统信号功能,以减轻抖动。外环是导纳控制,用于调节肘关节的动态行为,即其阻抗。进行仿真以验证所提出的控制方案的性能。

发现

结果表明,使用具有饱和功能的SMCDO可以有效消除传统SMC的颤动。此外,对于握手任务,还定义了阈值力和肘关节顺应性的值。然后,进行极限力测试,冲击测试和肘关节柔韧性测试。结果表明,在阻抗模型中,肘关节顺应性仅取决于刚度参数,而不取决于位置控制环。

实际影响

基于SMCDO的导纳控制的有效性可以在一定程度上提高工业机械手在不同工作环境下的适应性。

创意/价值

SMCDO完成轨迹跟踪的导纳控制比基于SMC的导纳控制具有更高的精度。

更新日期:2020-05-20
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