Model Predictive Control for Modeling and Simulation of Human Gait Motions

Authors

  • Vu Trieu Minh Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology, Estonia
  • Mart Tamre Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology, Estonia
  • Victor Musalimov Department of Mechatronics, Saint Petersburg State University of Information Technologies, Mechanics and Optics, Russia
  • Pavel Kovalenko Department of Mechatronics, Saint Petersburg State University of Information Technologies, Mechanics and Optics, Russia
  • Irina Rubinshtein Department of Mechatronics, Saint Petersburg State University of Information Technologies, Mechanics and Optics, Russia
  • Ivan Ovchinnikov Department of Mechatronics, Saint Petersburg State University of Information Technologies, Mechanics and Optics, Russia
  • Reza Moezzi Institute for Nanomaterials, Advanced Technologies and Innovation, Technical University of Liberec, Czech Republic

DOI:

https://doi.org/10.15157/IJITIS.2020.3.1.326-345

Keywords:

Human gait model, human gait plant, central nervous system, model predictive control, 5-link mechanism, motion capture system

Abstract

Human motion is a complex activity of the central nervous system (CNS) and muscles. Performance of a human motion can be decomposed into three components: estimation of trajectory; calculation of required signal for muscles; and performance of movement. The CNS conducts the first two tasks and the muscles perform the third task. This paper presents the development of a mathematical model and a Matlab Simulink plant for human gait movement. An internal model predictive control (MPC) is setup and plays as the human CNS to estimate the trajectory and to calculate the required signal for muscles to perform the movement. MPC calculates the required torques for each joint and generate optimal trajectories subject to human physical constraints for muscles. Results of simulation are analyzed and compared to the real human gait motions captured by a real motion capture system (Vicon). Finally, conclusions and recommendations from this research are withdrawn.

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Published

2020-01-15

How to Cite

Trieu Minh, V., Tamre, M., Musalimov, V., Kovalenko, P., Rubinshtein, I., Ovchinnikov, I., & Moezzi, R. (2020). Model Predictive Control for Modeling and Simulation of Human Gait Motions. International Journal of Innovative Technology and Interdisciplinary Sciences, 3(1), 326–345. https://doi.org/10.15157/IJITIS.2020.3.1.326-345