A Control Strategy for Pneumatically Powered Below-Hip Orthosis

IF 5.6 4区 医学 Q1 ENGINEERING, BIOMEDICAL
Irbm Pub Date : 2023-10-01 DOI:10.1016/j.irbm.2023.100791
Ashmi M , Akhil VM
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引用次数: 0

Abstract

Objectives

The role of controllers is inevitable in the design of powered orthosis to achieve ideal gait characteristics. Despite the fact that electrical actuators are preferred for most of the orthoses, a pneumatic actuator proves to have low cost and less weight. In this study, suitable controllers are designed and implemented for the knee and hip joints of a pneumatically actuated orthosis for the afflicted people.

Material and Methods

Different controllers (P, PI and PID) were tested for the position control of the orthosis by proper tuning of gain constants (KP, KI, KD). By using Lagrange Euler Method, the optimal trajectory for the knee and hip joints were determined for the pneumatic system. Particle swarm optimization (PSO) based PID controller was further employed for optimizing the gain constants.

Results

With the healthy gait as reference, the knee and hip reference angles were manually set in the PID controller. The subject was made to walk five times at a distance of 5 m and the average knee and hip angles were calculated based on the gait trials. Knee and hip angles varied 0 to 45° and 0 to 35° for healthy subjects while they varied 0 to 41° and 0 to 45° for the implemented pneumatic leg. The values of gain constants obtained in manual tuning matched with the PSO based controller at 25th iteration and the best fitness function was chosen with least error (0.7011).

Conclusion

The prototype of the orthosis is fabricated and the response of PID controller was found to be acceptable for a desired pressure (5 bar) with an angular velocity of 3 deg/s. Using a PID controlled pneumatic orthosis, exhibited less oscillation and showed an improved steady-state error when compared to the other controllers, thereby replicating healthy gait. A global best position with minimum error was obtained using PSO to find optimal controller gain constants.

Abstract Image

气动下髋关节矫形器的控制策略
目的在动力矫形器的设计中,控制器的作用是不可避免的,以实现理想的步态特征。尽管电动致动器对于大多数矫形器是优选的,但是气动致动器被证明具有低成本和较小重量。在这项研究中,为患者的气动矫形器的膝关节和髋关节设计并实现了合适的控制器。材料和方法通过适当调整增益常数(KP、KI、KD),测试了不同控制器(P、PI和PID)对矫形器位置的控制。利用拉格朗日-欧拉方法,确定了气动系统膝关节和髋关节的最优轨迹。进一步采用基于粒子群优化(PSO)的PID控制器对增益常数进行优化。结果以健康步态为参考,在PID控制器中手动设置膝关节和髋关节的参考角。受试者以5米的距离行走五次,并根据步态试验计算平均膝盖和臀部角度。健康受试者的膝关节和髋关节角度分别为0至45°和0至35°,而气动腿的膝关节角和髋关节角分别为0~41°和0~45°。手动调谐获得的增益常数值与基于PSO的控制器在第25次迭代时匹配,并以最小误差(0.7011)选择了最佳适应度函数。结论制作了矫形器的原型,发现PID控制器在角速度为3°/s的所需压力(5巴)下的响应是可接受的。与其他控制器相比,使用PID控制的气动矫形器,表现出较少的振荡,并显示出改进的稳态误差,从而复制了健康的步态。利用粒子群算法求解最优控制器增益常数,得到误差最小的全局最优位置。
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来源期刊
Irbm
Irbm ENGINEERING, BIOMEDICAL-
CiteScore
10.30
自引率
4.20%
发文量
81
审稿时长
57 days
期刊介绍: IRBM is the journal of the AGBM (Alliance for engineering in Biology an Medicine / Alliance pour le génie biologique et médical) and the SFGBM (BioMedical Engineering French Society / Société française de génie biologique médical) and the AFIB (French Association of Biomedical Engineers / Association française des ingénieurs biomédicaux). As a vehicle of information and knowledge in the field of biomedical technologies, IRBM is devoted to fundamental as well as clinical research. Biomedical engineering and use of new technologies are the cornerstones of IRBM, providing authors and users with the latest information. Its six issues per year propose reviews (state-of-the-art and current knowledge), original articles directed at fundamental research and articles focusing on biomedical engineering. All articles are submitted to peer reviewers acting as guarantors for IRBM''s scientific and medical content. The field covered by IRBM includes all the discipline of Biomedical engineering. Thereby, the type of papers published include those that cover the technological and methodological development in: -Physiological and Biological Signal processing (EEG, MEG, ECG…)- Medical Image processing- Biomechanics- Biomaterials- Medical Physics- Biophysics- Physiological and Biological Sensors- Information technologies in healthcare- Disability research- Computational physiology- …
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