Backstepping Control of Muscle Driven Systems with Redundancy Resolution
This addresses a gap in simulations for human-side dynamics in applications like rehabilitation and prosthetics, though it appears incremental as it builds on existing control methods for specific musculoskeletal models.
The paper tackles the lack of controllers for human dynamic models in human-machine interaction by introducing a feedback controller for muscle-driven systems, achieving arm movement, musculoskeletal dynamics, and muscle activations in a shoulder model with eight muscles and three degrees of freedom.
Due to the several applications on Human-machine interaction (HMI), this area of research has become one of the most popular in recent years. This is the case for instance of advanced training machines, robots for rehabilitation, robotic surgeries and prosthesis. In order to ensure desirable performances, simulations are recommended before real-time experiments. These simulations have not been a problem in HMI on the side of the machine. However, the lack of controllers for human dynamic models suggests the existence of a gap for performing simulations for the human side. This paper offers to fulfill the previous gap by introducing a novel method based on a feedback controller for the dynamics of muscle-driven systems. The approach has been developed for trajectory tracking of systems with redundancy muscle resolution. To illustrate the validation of the method, a shoulder model actuated by a group of eight linkages, eight muscles and three degrees of freedom was used. The controller objective is to move the arm from a static position to another one through muscular activation. The results on this paper show the achievement of the arm movement, musculoskeletal dynamics and muscle activations.