Combined feedforward and feedback control of a redundant, nonlinear, dynamic musculoskeletal system

Abstract

A functional electrical stimulation controller is presented that uses a combination of feedforward and feedback for arm control in high-level injury. The feedforward controller generates the muscle activations nominally required for desired movements, and the feedback controller corrects for errors caused by muscle fatigue and external disturbances. The feedforward controller is an artificial neural network (ANN) which approximates the inverse dynamics of the arm. The feedback loop includes a PID controller in series with a second ANN representing the nonlinear properties and biomechanical interactions of muscles and joints. The controller was designed and tested using a two-joint musculoskeletal model of the arm that includes four mono-articular and two bi-articular muscles. Its performance during goal-oriented movements of varying amplitudes and durations showed a tracking error of less than 4°in ideal conditions, and less than 10°even in the case of considerable fatigue and external disturbances.

Parametric synthesis of combined automatic regulating systems with digital PID­controllers

“…After calculating parameters of the regulator, it is usually necessary to manually adjust it to improve regulation quality. A similar approach is used in the medical field in development of a nonlinear dynamic combined system for controlling human musculoskeletal system [9]. The disturbance compensation regulator generates muscle activation for the desired movements and the regulator in the feedback loop corrects the errors caused by muscle fatigue and external disturbances.…”

Neuro-fuzzy models for hand movements induced by functional electrical stimulation in able-bodied and hemiplegic subjects

“…Another approach included ANNs in feedforward and feedback parts to model the inverse dynamics of the arm [24] . Expert systems based on fuzzy logic have been presented for other lower-limb FES applications such as rowing [25] or cycling [ 26 , 27 ].…”

A Muscle-Specific Rehabilitation Training Method of the Human Shoulder Based on the Optimal Load Orientation Concept

“…For the model of the shoulder, the typical representation of the muscles' lines of action was the line-segments model [11][12][13][14]. The models have been applied in several scenarios such as surgical simulation [13], wheelchair mechanics research [15,16], neuroprostheses control [17,18], etc. The direct purpose of these studies, focusing on the muscle forces, joint-contact forces and moment arms etc., was to reproduce and simulate muscle force generation patterns.…”