Model and neural control of leg cycling movement

Abstract

This paper proposes a neural control system for the leg cycling movement control. This system combines biological cybernetics and artificial control techniques together, which includes Central Pattern Generator (CPG), Artificial Neural Network (ANN) and impedance controller. Moreover, sensory feedback is incorporated to provide adaptivity and enhance feedback performance for the control system. A musculoskeletal model of lower limbs with 18 muscles and 6 bones is developed for simulation study. This system is not only suitable for the study of neural system and biomechanical system, it also has the potential for biomimetic robot design and rehabilitation engineering in future.