Lyapunov-Redesign and Sliding Mode Controller for Microprocessor Based Transfemoral Prosthesis

IF 2 4区 计算机科学 Q2 Computer Science
A. Murtaza, Muhammad Usman Qadir, Muhammad Awais Khan, Izhar ul Haq, Kamran Shah, Nizar Akhtar
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引用次数: 0

Abstract

Transfemoral prostheses have evolved from mechanical devices to microprocessor-based, electronically controlled knee joints, allowing amputees to regain control of their limbs. For improved amputee experience at varying ambulation rates, these devices provide controlled damping throughout the swing and stance phases of the gait cycle. Commercially available microprocessor-based prosthetic knee (MPK) joints use linear controllers, heuristic-based methods, and finite state machine based algorithms to track the refence gait cycle. However, since the amputee experiences a variety of non-linearities during ambulation, such as uneven terrains, walking backwards and climbing stairs, therefore, traditional controllers produces error, abnormal movements, unstable control system and require manual-tuning. As a result, novel controllers capable of replicating and tracking reference gait cycles for a range of reference signals are needed to reduce the burden on amputees and improve the rehabilitation process. Therefore, the current study proposes two non-linear control techniques, the Lyapunov-redesign controller and the sliding mode controller for real-time tracking of various signals, such as walking on level ground at a normal speed and ambulation on uneven terrains. State-space model of MPK was developed along with the mathematical modelling of non-linear controllers. Simulations and results are presented using MATLAB to verify the ability of proposed non-linear controllers for constantly and dynamically tracking and maintaining desired motion dynamics. Furthermore, for selected reference signals, a linear controller was applied to the same mathematical model of MPK. During tracking of reference angel in case of general gait cycle, an accuracy of 99.95% and 99.96% was achieved for sliding mode controller and Lyapunov-redesign controller respectively. Whereas, for the same case, linear controller had an accuracy of 95.5% only. Therefore, it can be concluded that the performance of non-linear controllers was better than their linear counterparts while tracking various reference signals for microprocessor based prosthetic knee. This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Intelligent Automation & Soft Computing DOI:10.32604/iasc.2022.020006 Article ech T Press Science
基于微处理器的经股假体lyapunov -重新设计和滑模控制器
经股骨假体已经从机械装置发展到基于微处理器的电子控制膝关节,使截肢者能够重新控制四肢。为了改善截肢者在不同行走速率下的体验,这些装置在步态周期的摆动和站立阶段提供可控的阻尼。商业上可用的基于微处理器的假膝(MPK)关节使用线性控制器、启发式方法和基于有限状态机的算法来跟踪参考步态周期。然而,由于截肢者在行走过程中会遇到各种非线性,如不平坦的地形、向后行走、爬楼梯等,因此,传统的控制器会产生误差,运动异常,控制系统不稳定,需要手动调谐。因此,需要能够复制和跟踪参考信号范围内参考步态周期的新型控制器来减轻截肢者的负担并改善康复过程。因此,本研究提出了两种非线性控制技术,即Lyapunov-redesign控制器和滑模控制器,用于实时跟踪各种信号,例如在平地上以正常速度行走和在不平坦的地形上行走。在建立非线性控制器数学模型的同时,建立了MPK的状态空间模型。利用MATLAB仿真和结果验证了所提出的非线性控制器持续动态跟踪和保持所需运动动力学的能力。此外,对于选定的参考信号,将线性控制器应用于MPK的相同数学模型。在一般步态周期下的参考角度跟踪中,滑模控制器和Lyapunov-redesign控制器的跟踪精度分别达到99.95%和99.96%。而在相同情况下,线性控制器的精度仅为95.5%。因此,对于基于微处理器的假膝,在跟踪各种参考信号时,非线性控制器的性能优于线性控制器。本作品采用知识共享署名4.0国际许可协议,允许在任何媒体上不受限制地使用、分发和复制,前提是正确引用原创作品。智能自动化与软计算DOI:10.32604/iasc.2022.020006 Article ech T Press Science
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来源期刊
Intelligent Automation and Soft Computing
Intelligent Automation and Soft Computing 工程技术-计算机:人工智能
CiteScore
3.50
自引率
10.00%
发文量
429
审稿时长
10.8 months
期刊介绍: An International Journal seeks to provide a common forum for the dissemination of accurate results about the world of intelligent automation, artificial intelligence, computer science, control, intelligent data science, modeling and systems engineering. It is intended that the articles published in the journal will encompass both the short and the long term effects of soft computing and other related fields such as robotics, control, computer, vision, speech recognition, pattern recognition, data mining, big data, data analytics, machine intelligence, cyber security and deep learning. It further hopes it will address the existing and emerging relationships between automation, systems engineering, system of systems engineering and soft computing. The journal will publish original and survey papers on artificial intelligence, intelligent automation and computer engineering with an emphasis on current and potential applications of soft computing. It will have a broad interest in all engineering disciplines, computer science, and related technological fields such as medicine, biology operations research, technology management, agriculture and information technology.
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