A robust control strategy aided with RBF neural network for variable stiffness elastic actuators
The rehabilitation robots based on variable stiffness elastic actuators integrated flexible drive and variable stiffness output for excellent human-robot interaction.To ensure smooth rehabilitation and overcome modeling and control challenges,the design takes into account the dynamic model of the actuator under its own gravity and disturbance effects.A radial basis function network is utilized to approximate the actual dynamics model for accurate tracking of output position and stiffness.
NETL
NSTL
万方数据
