Adaptive RBF neural network-computed torque control for a pediatric gait exoskeleton system: an experimental study

• Published in: Intelligent service robotics Vol. 16; no. 5; pp. 549 - 564
• Main Authors: Narayan, Jyotindra, Abbas, Mohamed, Patel, Bhavik, Dwivedy, Santosha K.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2023; Springer Nature B.V
• Subjects: Ankle; Approximation; Artificial Intelligence; Carbon fibers; Computation; Control; Correlation coefficients; Coupled modes; Design; Dynamical Systems; Engineering; Exoskeletons; Gait; Mechatronics; Muscular function; Neural networks; Original Research Paper; Pediatrics; Radial basis function; Rehabilitation; Robotics; Robotics and Automation; Robots; Robust control; Simulation; Torque; Tracking control; User Interfaces and Human Computer Interaction; Vibration; Lyapunov stability; Gait rehabilitation; Pediatric exoskeleton; Radial basis function neural network

For pediatric rehabilitation, obtaining accurate coupled human-exoskeleton system models is challenging due to unknown model parameters caused by children’s dynamic growth and development. These factors make it difficult to establish precise and standardized models for exoskeleton control. Additiona...