|
| Adaptive CMAC neural network robust control for flexible joints space robot with friction characteristics |
| Received:October 05, 2020 Revised:February 16, 2021 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7511/jslx20201005002 |
| KeyWord:space robot flexible-joint CMAC nonlinear friction robust control |
| Author | Institution |
| 尤鑫烨 |
福州大学 机械工程及自动化学院, 福州 |
| 陈力 |
福州大学 机械工程及自动化学院, 福州 |
|
| Hits: 623 |
| Download times: 259 |
| Abstract: |
| The dynamic control of a floating space robot system with flexible joints under the influence of joint friction torques is discussed.A CMAC robust controller based on Gaussian basis function and friction torque compensator are proposed.The singular perturbation theory is used to decompose the dynamic model of the system into fast and slow subsystems.A torque differential feedback controller is designed for the fast subsystem to suppress the vibration caused by the joint flexibility of the manipulator.For the slow subsystem,a robust controller based on adaptive CMAC neural network is designed to realize the joint trajectory tracking under the condition of uncertain parameters of the system,and a compensator based on the upper bound of friction force is designed to eliminate the influence of friction torque.Compared with the traditional CMAC neural network control,the proposed controller can effectively improve the hysteresis problem caused by nonlinear joint friction,and has the ability to track the desired trajectory quickly and accurately.The stability of the controller is proved by Lyapunov stability theory.The effectiveness of the scheme is verified by the simulation results. |