Predictive Control of Peak Achilles Tendon Force in a Simulated System of the Human Ankle Joint with a Parallel Artificial Actuator during Hopping

Mahdi Nabipour, Gregory Sawicki, M. Sartori

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

Latest advances in wearable exoskeletons for the human lower extremity predominantly focus on minimising metabolic cost of walking. However, there currently is no robotic exoskeleton that gains control on the mechanics of biological tissues such as biological muscles or series-elastic tendons. Achieving robotic control of biological tissue mechanics would enable prevention of musculoskeletal injuries or the personalization of rehabilitation treatments following injury with levels of precisions not attained before. In this paper, we introduce a new framework that uses nonlinear model predictive control (NMPC) for the closed-loop control of peak tendon force in a simulated system of the human ankle joint with parallel exoskeletal actuation. We propose a computationally efficient NMPC’s inner model consisting of explicit, closed-form equations of muscle-tendon dynamics along with those of the ankle joint with parallel actuation. The proposed formulation is tested and verified on movement data collected during dynamic ankle dorsiflexion/plantarflexion rotations executed on a dynamometer as well as during walking and running on a treadmill. The framework designed using the NMPC controller showed a promising performance in keeping the Achilles tendon force under a predefined threshold. Results indicated that our proposed model was generalizable to different muscles and gaits and suitable for real-time applications due to its low computational time.
Original languageEnglish
Title of host publicationIEEE International Conference on Rehabilitation Robotics 2023
PublisherIEEE
ISBN (Electronic)9798350342758
DOIs
Publication statusPublished - 28 Sept 2023
Event18th IEEE International Conference on Rehabilitation Robotics, ICORR 2023 - Singapore, Singapore
Duration: 24 Sept 202328 Sept 2023
Conference number: 18

Conference

Conference18th IEEE International Conference on Rehabilitation Robotics, ICORR 2023
Abbreviated titleICORR 2023
Country/TerritorySingapore
CitySingapore
Period24/09/2328/09/23

Keywords

  • Modeling
  • muscle modeling
  • Predicitive control
  • Model predictive control
  • Soleus muscle
  • Regression
  • Exoskeleton control
  • Assistive device
  • Ankle foot orthosis
  • Hill-type muscle

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