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صفحه اصلی
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سی و یکمین کنفرانس بین المللی مهندسی برق
Robot-Assisted Rehabilitation with Optimal Impedance: Using an $\mathcal{EKF}$-Based $\mathcal{L}asso-\mathcal{MPC}$
نویسندگان :
Hossein Ahmadian
1
Iman Sharifi
2
Heidar Ali Talebi
3
1- دانشگاه صنعتی امیرکبیر(پلی تکنیک تهران)
2- دانشگاه صنعتی امیرکبیر(پلی تکنیک تهران)
3- دانشگاه صنعتی امیرکبیر(پلی تکنیک تهران)
کلمات کلیدی :
Extended Kalman Filter ($\mathcal{EKF}$)،$\mathcal{L}asso$ Regression, Model Predictive Control ($\mathcal{MPC}$)،$\mathcal{L}asso-\mathcal{MPC}$،Robot-Assisted Rehabilitation
چکیده :
Wearable robots are crucial for helping patients with lower limb diseases, particularly those with trouble walking since their numbers are rising. These robots assist patients in walking, provide comfort, and aid in recuperation. In this study, the model predictive control based on the Lasso regression theory ($\mathcal{L}asso-\mathcal{MPC}$) and the extended Kalman filter ($\mathcal{EKF}$) was used to make a controller that helps the patient walk by adjusting the impedance so that, in addition to regular walking, the patient has to put out the most effort when walking. The simulation results demonstrate the suggested control's incredible effectiveness in robot-assisted rehabilitation.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 43.6.0
