Literature DB >> 32865604

Optimal time-varying postural control in a single-link neuromechanical model with feedback latencies.

Kamran Iqbal1.   

Abstract

Maintaining balance during quiet standing is a challenging task for the neural control mechanisms due to the inherent instabilities involved in the task. The feedback latencies and the lowpass characteristics of skeletal muscle add to the difficulty of regulating postural dynamics in real-time. Inverted-pendulum (IP) type robotic models have served as a popular paradigm to investigate control of postural balance. In this study, an in-depth neuromechanical postural control model is developed from physiological principles. The model comprises a single-segment IP robotic model, Hill-type muscle model, and proprioceptive feedback from the muscle spindle (MS) and golgi tendon organ (GTO). An optimal proportional-integral-derivative (PID) controller is proposed to realize effective postural control amid latencies in sensory feedback. The neural commands for postural stabilization are generated by a time-varying PID controller, tuned using linear quadratic regulator (LQR) principles. Computer simulations are used to assess the efficacy of the tuned PID-LQR controller. Sensitivity analysis of the controlled system shows a delay tolerance of 300ms. Preliminary empirical data in support of the mathematical model were obtained from perturbation experiments. The model response to perturbation torque, measured in terms of the center of mass (COM) excursion in the anterior-posterior (AP) direction, displays a high degree of correlation with the empirical data ([Formula: see text]).

Entities:  

Keywords:  Feedback latencies; Inverted-pendulum; Neuromechanical postural control model; Optimally tuned PID controller

Year:  2020        PMID: 32865604     DOI: 10.1007/s00422-020-00843-9

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  1 in total

1.  Nonlinear postural control paradigm for larger perturbations in the presence of neural delays.

Authors:  Nadia Sultan; Muhammad Najam Ul Islam; Asif Mahmood Mughal
Journal:  Biol Cybern       Date:  2021-08-09       Impact factor: 2.086

  1 in total

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