scholarly journals A Nested-Loop Iterative Learning Control for Robot Manipulators

2019 ◽  
Vol 52 (15) ◽  
pp. 358-363
Author(s):  
Yu-Hsiu Lee ◽  
Sheng-Chieh Hsu ◽  
Yan-Yi Du ◽  
Jwu-Sheng Hu ◽  
Tsu-Chin Tsao
Keyword(s):  
Iterative Learning Control ◽  
Robot Manipulators ◽  
Learning Control ◽  
Iterative Learning ◽  
Nested Loop

D-type iterative learning control without resetting condition for robot manipulators

Robotica ◽  
2011 ◽  
Vol 29 (7) ◽  
pp. 975-980 ◽  
Author(s):  
Farah Bouakrif
Keyword(s):  
Iterative Learning Control ◽  
Robot Manipulators ◽  
Learning Control ◽  
Iterative Learning ◽  
Time Interval ◽  
Initial State ◽  
External Disturbances ◽  
Repetitive Tasks ◽  
Control Scheme ◽  
Topological Measure

SUMMARYThis paper deals with iterative learning control (ILC) design to solve the trajectory tracking problem for rigid robot manipulators subject to external disturbances, and performing repetitive tasks. A D-type ILC is presented with an initial condition algorithm, which gives the initial state value in each iteration automatically. Thus, the resetting condition (the initial state error is equal to zero) is not required. The λ-norm is adopted as the topological measure in our proof of the asymptotic stability of this control scheme, over the whole finite time-interval, when the iteration number tends to infinity. Simulation results are presented to illustrate the effectiveness of the proposed control scheme.

Adaptive Iterative Learning Control for Robot Manipulators with Initial Resetting Errors

2011 ◽  
Vol 130-134 ◽  
pp. 265-269 ◽  
Author(s):  
Jian Ming Wei ◽  
Yun An Hu
Keyword(s):  
Iterative Learning Control ◽  
Robot Manipulators ◽  
Error Function ◽  
Tracking Error ◽  
Learning Control ◽  
Iterative Learning ◽  
Unknown Parameters ◽  
Adaptive Iterative Learning Control ◽  
Suitable Parameter ◽  
Parameter Values

In this paper, an adaptive iterative learning control is presented for robot manipulators with unknown parameters, performing repetitive tasks. In order to overcome the initial resetting errors, an auxiliary tracking error function is introduced. The adaptive algorithm is derived along the iteration axis to search for suitable parameter values. The technical analysis shows convergence of the tracking errors. Finally, simulation results are provided to illustrate the effectiveness of the proposed controller.

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