Robust Adaptive Iterative Learning Control for High-Precision Attitude Tracking of Spacecraft

2021 ◽  
Vol 34 (1) ◽  
pp. 04020108
Author(s):  
Qijia Yao
2014 ◽  
Vol 6 ◽  
pp. 201317 ◽  
Author(s):  
Guofeng Tong ◽  
Mingxiu Lin

This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.


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