耿艳利, 武正恩, 刘作军, 陈亚伟. 基于时延估计的动力型下肢假肢分段控制策略研究[J]. 信息与控制, 2021, 50(5): 566-573. DOI: 10.13976/j.cnki.xk.2021.1043
引用本文: 耿艳利, 武正恩, 刘作军, 陈亚伟. 基于时延估计的动力型下肢假肢分段控制策略研究[J]. 信息与控制, 2021, 50(5): 566-573. DOI: 10.13976/j.cnki.xk.2021.1043
GENG Yanli, WU Zheng'en, LIU Zuojun, CHEN Yawei. Study on Subsection Control Strategy of Active Lower Limb Prosthesis with Time Delay Estimation[J]. INFORMATION AND CONTROL, 2021, 50(5): 566-573. DOI: 10.13976/j.cnki.xk.2021.1043
Citation: GENG Yanli, WU Zheng'en, LIU Zuojun, CHEN Yawei. Study on Subsection Control Strategy of Active Lower Limb Prosthesis with Time Delay Estimation[J]. INFORMATION AND CONTROL, 2021, 50(5): 566-573. DOI: 10.13976/j.cnki.xk.2021.1043

基于时延估计的动力型下肢假肢分段控制策略研究

Study on Subsection Control Strategy of Active Lower Limb Prosthesis with Time Delay Estimation

  • 摘要: 动力型下肢假肢具有较强的非线性、耦合性,很难建立其精确的动力学模型,因此增加了假肢控制的难度.针对此问题,研究了基于时延估计(TDE)的动力型下肢假肢分段控制策略.首先利用VICON MX 3维步态分析系统采集下肢运动信息,根据足底压力将假肢穿戴者的正常步态划分为两个模态分别为支撑相和摆动相;其次,基于拉格朗日方程建立假肢摆动相和支撑相的动力学模型;然后,提出一种分段控制策略,摆动相采用基于TDE的滑模控制,支撑相将上述方法与目标阻抗控制相结合,研究基于TDE的目标阻抗滑模控制;最后,分别将基于TDE的滑模控制与基于模型的滑模控制方法应用于各关节轨迹的跟踪控制.仿真结果表明,方法可以对下肢假肢系统中强非线性以及各种不确定因素进行补偿,简化模型计算,并且提高假肢的控制效果.

     

    Abstract: The lower limb prosthesis has severe nonlinearities and coupling such that an accurate dynamic model is difficult to build, making it very challenging to control the prosthesis. Hence, a subsection control strategy is proposed to resolve these difficulties. First, the VICON MX 3D gait analysis system is used to collect the lower limb movement information, and then the gait of the sound section is divided into stance and swing phases based on plantar pressure. Next, the dynamic model of the two stages is established based on the Lagrange equation. Furthermore, a subsection control strategy is developed. Then, based on TDE, sliding mode control is studied in the swing phase and combined with the target impedance control used in the stance phase. Finally, compared with the model-based sliding control method, the motion trajectories of each joint are tracked. The simulation results showed that the proposed method can compensate for the strong nonlinearity and various uncertain factors in the lower limb prosthesis system, simplify the calculation of the model, and improve the control effect of the prosthesis.

     

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