Control of an Anthropomorphic Prosthetic Arm Using EMG Signals

نوع: Type: thesis

مقطع: Segment: masters

عنوان: Title: Control of an Anthropomorphic Prosthetic Arm Using EMG Signals

ارائه دهنده: Provider: Elham Farahi

اساتید راهنما: Supervisors: Hamidreza Karami (Ph.D) - Manouchehr Hosseini Pilangorgi (Ph.D)

اساتید مشاور: Advisory Professors: Mohammad Amin Ghasemi (Ph.D) Nader Farahpoor (Ph.D)

اساتید ممتحن یا داور: Examining professors or referees:

زمان و تاریخ ارائه: Time and date of presentation: Summer 2020

مکان ارائه: Place of presentation:

چکیده: Abstract: The EMG signal, which is obtained from the natural or artificial stimulation of the body's muscles, is used in the medical examination of diseases and musculoskeletal and ergonomic injuries and the production of related products. In the field of robotics, this signal is used to manage and control artificial and robotic organs. EMG signal analysis allows direct examination of the muscles. The artificial arm or robot must have sufficient degree of freedom to respond to the commands of the body's nervous system and perform similar behaviors to the natural arm. To this end, EMG data are collected and efforts are made to improve the behavior of the artificial arm by improving the mechanical design or improving the control system. The goal is to use a controller that is able to adapt and update the parameters, to have proper control over the artificial arm, and to behave similarly to the human arm. To achieve this goal, the degree of freedom required to perform movements is created by using advanced controllers and operators, which are often servomotors or mechanical jacks. Adaptive control is a method used for systems with indefinite parameters or with variable parameters over time so that there is no need to redesign the control system due to changing parameters. The idea of ​​using adaptive control of the reference model based on Liapanov's theory to ensure closed-loop stability and optimal performance in the presence of model uncertainties, time-varying parameters and uncertainties and noise, has been used in this study. To use the EMG signal to control the robotic or artificial arm, modeling the movement of the human arm based on mathematical equations has been performed and a suitable and accurate model has been created to repeat the behavioral pattern of the arm. After modeling and control design, the mathematical properties of the simulation signals were extracted and compared with the mathematical characteristics of the EMG signal, and the model's behavior was approached to the natural ar

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