摘要本论文是对本次毕业设计所选择的课题—康复医疗机器人系统自抗扰控制应用研究的一个详细论述和总结。现代社会中，脑中风已经严重威胁中老年人身体健康并且发病率正逐年上升。这种疾病引发了患者肢体运动功能的丧失，很大程度上影响了患者日常生活的能力。机器人技术在医疗康复领域的应用，不仅提高了病人康复的科学性和针对性，使得病人更好更快地康复，而且还会缓解紧张的医师资源。66196
自抗扰控制技术是由中科院韩京清提出的开创性技术，在一定程度上颠覆了控制工程中的模型化方法，具备自抗扰控制器的康复机器人在未知强非线性和不确定强扰动作用下能保证良好的控制精度。
本文的主要工作：
1. 分析康复机器人Armeo的肌肉-手臂-机械臂组合模型动力学构造，推导其拉格朗日方程并建模。
2. 在康复机器人Armeo模型基础上设计PID控制器并完成仿真。
3. 在康复机器人Armeo模型基础上设计自抗扰控制器并完成轨迹跟踪，将仿真结果与PID控制器相比较。
仿真结果表明，相较于传统的PID控制器，ADRC控制器具有稳定快、超调小的优势，具备更好的抗干扰能力。
毕业论文关键词 Armeo中风康复机器人 肌肉-手臂-机械臂模型 PID 自抗扰
毕业设计说明书（论文）外文摘要
Title Research of robotic-assisted stroke rehabilitation system with ADRC control law
Abstract
This essay is a summary and an explanation of the subject of this graduation design, which is ‘Research of robotic-assisted stroke rehabilitation system with ADRC control law’. Stroke is a serious threat to the health of the elderly,which leads to the loss of motor function in patients and related complications, especially the loss of upper limb motor function, which greatly affects the patient's daily life.
The combination of the development of robot technology and clinical rehabilitation medicine provided a good opportunity for rehabilitative robot research. A robot equipped with an ADRC controller can guarantee good control accuracy in unknown strongly nonlinear and uncertain disturbance conditions.
The main work of this essay:
1. Analyze the rehabilitation robot’s muscle-arm-robotic arm dynamics model structure and derived its model with Lagrange equation modeling.
2. On the basis of the model structure, design and perform ADRC trajectory tracking.
3. Design and implement PID trajectory tracking and compare it with ADRC.
Simulation results show that compared with conventional PID controller, the ADRC controller has the advantages of rapid stabilization, smaller overshoot and more robust to uncertain disturbances.
Key words Armeo stroke rehabilitation robot muscle-arm model PID ADRC
目录
1 绪论 1
1.1 课题背景 1
1.2 突破性的创新—自抗扰技术 2
1.3 本文主要工作 3
2 肌肉模型和手臂-机械臂系统模型 4
2.1 肌肉模型 5
2.2手臂-机械臂组合模型 5 康复医疗机器人Armeo系统自抗扰控制应用研究:http://www.youerw.com/zidonghua/lunwen_74011.html