Control method for space manipulator with external disturbance based on recurrent fuzzy neural networks

ZHANG Ruifen

(Department of Hydraulic Engineering, Fujian College of Water Conservancy and Electric Power, Yongan 366000, China)

Abstract: Aiming at the control problem of space manipulator system with external disturbance and uncertain parameters when the attitude of based was controlled and its location was uncontrolled, combining with the system of conservation of momentum, the system's dynamic model under external disturbance was established by using the Lagrange dynamics equation and assumed modes methods were investigated. A method based on recurrent fuzzy neural networks was proposed. This method could solve space manipulators with external disturbance and uncertain parameters control problems, and through the second Lyapunov method to prove the asymptotic stability of the closedloop control system. The results indicate that this control strategy has better tracking performance and higher reliability than the computed torque control method through the computer numerical simulation experiment.

Key words: space manipulators; recurrent fuzzy neural networks; uncertain parameters; external disturbance