Open AccessFuzzy sliding‐mode control of a human arm in the sagittal plane with optimal trajectory
Author(s) -
Ardakani Fateme Fotouhi,
Vatankhah Ramin,
Sharifi Mojtaba
Publication year - 2018
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.2018-0067
Subject(s) - trajectory , control theory (sociology) , sagittal plane , fuzzy logic , torque , controller (irrigation) , human arm , sliding mode control , computer science , exponential function , optimal control , engineering , mathematics , simulation , control (management) , nonlinear system , physics , mathematical optimization , artificial intelligence , anatomy , medicine , astronomy , quantum mechanics , mathematical analysis , biology , agronomy , thermodynamics
Patients with spinal cord injuries cannot move their limbs using their intact muscles. A suitable controller can be used to move their arms by employing the functional electrical stimulation method. In this article, a fuzzy exponential sliding‐mode controller is designed to move a musculoskeletal human arm model to track an optimal trajectory in the sagittal plane. This optimal arm trajectory is obtained by developing a policy for the central nervous system. In order to specify the optimal trajectory between two points, two dynamic and static optimal criteria are applied simultaneously. The first dynamic objective function is defined to minimize the joint torques, and the second static optimization is offered to minimize the muscle forces at each moment. In addition, fuzzy logic is used to tune the sliding‐surface parameter to enable an appropriate tracking performance. Simulation results are evaluated and compared with experimental data for upward and downward movements of the human arm.