中文版 | English
题名

动力大腿假肢多地形自适应控制研究

其他题名
RESEARCH ON MULTI-TERRAIN ADAPTIVE CONTROL OF POWERED TRANSFEMORAL PROSTHESES
姓名
姓名拼音
YIN Shucong
学号
12132314
学位类型
硕士
学位专业
0801Z1 智能制造与机器人
学科门类/专业学位类别
08 工学
导师
付成龙
导师单位
机械与能源工程系
论文答辩日期
2024-05-10
论文提交日期
2024-06-25
学位授予单位
南方科技大学
学位授予地点
深圳
摘要

       近年来动力大腿假肢的研究取得了显著进步,已能帮助截肢者实现平地、上/下斜坡、上/下楼梯等多种运动。然而现有控制器多是为单一地形的单一任务设计。不同任务如变速行走需研究人员手动调整控制器参数,这无法满足截肢者日常多地形连续行走的要求。此外大多数动力假肢不具备感知环境和人体行走信息的功能,因而无法给控制器的切换提供指导。

      为了解决上述问题,本文提出使用深度相机和惯性测量单元对截肢者的下一步地形进行预测,建立多地形不同任务的统一控制算法。根据感知的环境信息和人体行走信息实时切换相应的控制参数,实现假肢多地形不 同任务的稳定行走和平滑过渡。

      针对实验室第二代动力大腿假肢存在的零件配合不合理和电气系统复杂问题,本文搭建了实验室第三代动力大腿假肢。主要工作包括机械结构优化、关键零部件选型和电气控制系统设计。其次将环境识别和速度估计算法分别封装成单独的模块,提高假肢控制的实时性和稳定性。

      基于人体行走过程中的下肢关节运动学特征,本文提出了使用截肢者残余大腿控制假肢运动的连续相位控制策略。构建适用于多地形的分段单调相位变量和免调参的虚拟约束模型。使用截肢者残肢的运动角度估计步态相位,再结合预测的任务条件通过虚拟约束模型生成期望的关节角度, 实现了截肢者对假肢的意图控制。

      结合健康人多地形不同任务的关节角度和力矩数据,本文提出了任务自适应的准刚度控制算法。利用高斯过程和高斯混合模型学习不同任务与关节角度-力矩曲线之间的概率分布。使用内核化运动原语模型生成新任务条件下的关节角度-力矩曲线。控制器根据支撑相的分段线性拟合每个子阶段的控制参数,实现了新任务条件下阻抗参数的自动生成。

      最后本文搭建了动力大腿假肢多地形测试平台,设计截肢者多地形不同任务的行走实验。通过对比主动假肢和被动假肢的数据,证明本研究所提出的方法能够帮助截肢者实现多地形不同任务的稳定行走并减少截肢者27%-40%的新陈代谢消耗,提高截肢者的步态对称性。

其他摘要

      Recent research of powered transfemoral prostheses has achieved advancements in helping amputees perform walking on level ground, up/down slopes, and up/down stairs. However, most existing controllers are designed for a specific task on a specific terrain. Different tasks such as various-speed walking need researcher to manually adjust the prosthesis’ parameters, which fails to meet the needs of amputees for daily continuous walking across various terrains. Moreover, most powered prostheses lack the ability to perceive the environment and human walking information, thus unable to provide guidance for the switch of the controller.

      To solve the above issues, this paper proposed to use a depth camera and inertial measurement unit to predict the terrain type in front of amputees, establish a unified control algorithm for different tasks of multi-terrain. Real time switching of control parameters is achieved based on perceived environmental information and human walking information, ensuring stable walking and smooth transition for powered prosthesis across different terrains and tasks.

      The third generation of power transfemoral prosthesis was designed to solve the structure and electrical issues of the second generation of power transfemoral prosthesis, including optimizing the unreasonable mechanical structure and designing the electrical control system. The environment recognition and velocity estimation algorithms are packaged into separate modules to improve the real time performance and stability of prosthetic control.

      Based on the kinematic characteristics of the lower limb joints during walking, this research proposed a continuous-phase control strategy using the amputee's residual thigh to control the prosthesis locomotion in the swing phase. A piecewise monotonic phase variable and tuning-free virtual constraint model were constructed for multi-terrain. Besides, the angle of the amputee's residual thigh was used to estimate the gait phase, and the desired joint angle was generated by the virtual constraint model combined with the predicted task feature, which realizes the amputee's volitional control of the prosthesis.

      Based on the joint angle and torque data of able-bodied people in multi terrain and different tasks, this paper proposed a task adaptive quasi-stiffness control strategy. Gaussian Process and Gaussian Mixture Model are used to learn the probability distribution between task conditions and joint angle-torque curves. The Kernelized Movement Primitive Model is used to generate the joint angle torque curve under the new task. The controller fits the control parameters of each sub-phase according to the piecewise linear of the stance phase, which realizes the automatic generation of impedance parameters under new task conditions.

      Finally, this paper established a multi-terrain experimental platform for powered transfemoral prosthesis and designed the walking experiments with different tasks on various terrains for an amputee. By comparing data on passive and powered prosthesis, it demonstrated that the proposed method could help amputee achieve stable multi-terrain walking with different tasks, reduce the metabolic cost of amputee by 27% to 40%, and improve the gait symmetry of amputee.

关键词
其他关键词
语种
中文
培养类别
独立培养
入学年份
2021
学位授予年份
2024-06
参考文献列表

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尹树丛. 动力大腿假肢多地形自适应控制研究[D]. 深圳. 南方科技大学,2024.
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