System Identification and Two-Degree-of-Freedom Control of Nonlinear, Viscoelastic Tissues

IEEE Trans Biomed Eng. 2022 Dec;69(12):3803-3811. doi: 10.1109/TBME.2022.3179655. Epub 2022 Nov 21.

Abstract

Objective: This paper presents a force control scheme for brief isotonic holds in an isometrically contracted muscle tissue, with minimal overshoot and settling time to measure its shortening velocity, a key parameter of muscle function.

Methods: A two-degree-of-freedom control configuration, formed by a feedback controller and a feedforward controller, is explored. The feedback controller is a proportional-integral controller and the feedforward controller is designed using the inverse of a control-oriented model of muscle tissue. A generalized linear model and a nonlinear model of muscle tissue are explored using input-output data and system identification techniques. The force control scheme is tested on equine airway smooth muscle and its robustness confirmed with murine flexor digitorum brevis muscle.

Results: Performance and repeatability of the force control scheme as well as the number of inputs and level of supervision required from the user were assessed with a series of experiments. The force control scheme was able to fulfill the stated control objectives in most cases, including the requirements for settling time and overshoot.

Conclusion: The proposed control scheme is shown to enable automation of force control for characterizing muscle mechanics with minimal user input required.

Significance: This paper leverages an inversion-based feedforward controller based on a nonlinear physiological model in a system identification context that is superior to classic linear system identification. The control scheme can be used as a steppingstone for generalized control of nonlinear, viscoelastic materials.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Automation
  • Feedback
  • Horses
  • Linear Models
  • Mice
  • Musculoskeletal Physiological Phenomena*
  • Nonlinear Dynamics*