Optimal control of human‐like musculoskeletal arm: Prediction of trajectory and muscle forces. (29th March 2016)
- Record Type:
- Journal Article
- Title:
- Optimal control of human‐like musculoskeletal arm: Prediction of trajectory and muscle forces. (29th March 2016)
- Main Title:
- Optimal control of human‐like musculoskeletal arm: Prediction of trajectory and muscle forces
- Authors:
- Sharifi, Mojtaba
Pourtakdoust, Seid H.
Parnianpour, Mohamad - Abstract:
- Summary: Optimal trajectory and muscle forces of a human‐like musculoskeletal arm are predicted for planar point‐to‐point movements using optimal control theory. The central nervous system (CNS) is modeled as an optimal controller that performs a reaching motion to final states via minimization of an objective function. For the CNS strategy, a cubic function of muscles stresses is considered as an appropriate objective function that minimizes muscles fatigue. A two‐DOF nonlinear musculoskeletal planar arm model with four states and six muscle actuators is used for the evaluation of the proposed optimal strategy. The nonlinear variational formulation of the corresponding optimal control problem is developed and solved using the method of variation of extremals. The initial and (desired) final states (position and velocity) are used as input kinematic information, while the problem constraints include the motion range of each joint, maximum allowable muscle tension, and stability requirements. The resulting optimal trajectories are compared with experimental data as well as those corresponding to recent researches on model predictions of human arm movements. It is demonstrated that the proposed optimal control strategy using minimum fatigue criterion is more realistic in prediction of motion trajectories in comparison with previous work that has utilized minimum joints' torque criterion. Accordingly, minimization of muscles fatigue is an effective biomechanical criterion forSummary: Optimal trajectory and muscle forces of a human‐like musculoskeletal arm are predicted for planar point‐to‐point movements using optimal control theory. The central nervous system (CNS) is modeled as an optimal controller that performs a reaching motion to final states via minimization of an objective function. For the CNS strategy, a cubic function of muscles stresses is considered as an appropriate objective function that minimizes muscles fatigue. A two‐DOF nonlinear musculoskeletal planar arm model with four states and six muscle actuators is used for the evaluation of the proposed optimal strategy. The nonlinear variational formulation of the corresponding optimal control problem is developed and solved using the method of variation of extremals. The initial and (desired) final states (position and velocity) are used as input kinematic information, while the problem constraints include the motion range of each joint, maximum allowable muscle tension, and stability requirements. The resulting optimal trajectories are compared with experimental data as well as those corresponding to recent researches on model predictions of human arm movements. It is demonstrated that the proposed optimal control strategy using minimum fatigue criterion is more realistic in prediction of motion trajectories in comparison with previous work that has utilized minimum joints' torque criterion. Accordingly, minimization of muscles fatigue is an effective biomechanical criterion for the CNS in prediction of point‐to‐point human arm motions. Copyright © 2016 John Wiley & Sons, Ltd. … (more)
- Is Part Of:
- Optimal control applications and methods. Volume 38:Number 2(2017)
- Journal:
- Optimal control applications and methods
- Issue:
- Volume 38:Number 2(2017)
- Issue Display:
- Volume 38, Issue 2 (2017)
- Year:
- 2017
- Volume:
- 38
- Issue:
- 2
- Issue Sort Value:
- 2017-0038-0002-0000
- Page Start:
- 167
- Page End:
- 183
- Publication Date:
- 2016-03-29
- Subjects:
- optimal control -- nonlinear musculoskeletal arm -- minimum fatigue criterion -- variation of extremals (VE)
Control theory -- Periodicals
Mathematical optimization -- Periodicals
629.8312 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/oca.2249 ↗
- Languages:
- English
- ISSNs:
- 0143-2087
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6275.070000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 1751.xml