Dual time scale combination control of flexible manipulator driven by reinforcement learning
LIU Cheng-yan
HU Jian
YAO Jian-yong
TAN Tian-le
LIU Yu
LIN Jia-wei
Abstract：In this paper,the trajectory tracking and vibration suppression of flexible manipulators are studied.Firstly,the dynamic model of the flexible manipulator is established based on Lagrange method and assumed mode method.Then,the model is decomposed into a slow time scale subsystem to describe the rigid body motion and a fast time scale sub-system to describe the flexible vibration by using the singular perturbation theory.For the rigid body subsystem,a rigid composite controller based on sliding mode variable structure,radial basis neural network to estimate model parameters,and disturbance observer to estimate disturbance and model uncertainty is established;the fast subsystem establishes a flexible controller that uses reinforcement learning and optimal control to obtain the optimal control solution online.The stability of the system under different time scales is proved by Lyapunov stability theory,and the controller under different time scales is superimposed to obtain the combined controller of the original system state.Finally,the experimental results show that the proposed combined control method is superior.
Keywords：flexible manipulatortrajectory trackingvibration suppressionneural networkdisturbance observerreinforcement learning
Publication Date：2025-03-31
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：12( 541-552 )