2011
DOI: 10.1017/s0263574711000191
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D-type iterative learning control without resetting condition for robot manipulators

Abstract: 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 stabili… Show more

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Cited by 26 publications
(14 citation statements)
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“…The NI-USB 6009 is setup to use the QET's analog command port to drive the motor's control/input signal and the QET's analog tachometer port as the motor's response/output speed signal, and finally the NI-USB is C. Numerical simulations 1) Control of a DC motor: In this part, we assume that the motor dynamics is subject to a nonlinear friction verifying all the conditions imposed to system (6). The friction is assumed to be a Lipschitz function of the speed with unknown parameters.…”
Section: B Real-time Control Using Ni Usb-6009mentioning
confidence: 99%
See 1 more Smart Citation
“…The NI-USB 6009 is setup to use the QET's analog command port to drive the motor's control/input signal and the QET's analog tachometer port as the motor's response/output speed signal, and finally the NI-USB is C. Numerical simulations 1) Control of a DC motor: In this part, we assume that the motor dynamics is subject to a nonlinear friction verifying all the conditions imposed to system (6). The friction is assumed to be a Lipschitz function of the speed with unknown parameters.…”
Section: B Real-time Control Using Ni Usb-6009mentioning
confidence: 99%
“…Subsequently, iterative learning control has been further explored in many engineering areas as robotics [23], [6], [14], multi-agent control [15], mechatronics [13], motor control applications [5], [22] and more. Referring to the extensive literature in this area of research, it has been shown that iterative-learning procedures can be implemented for continuous-time systems [20], [25] and discrete-time systems as well [16], [18], [24], [21].…”
Section: Introductionmentioning
confidence: 99%
“…Over the last two decades, this technique has been the center of interest of many researchers. [2][3][4][5][6][7][8][9][10][11][12][13][14][15] dead-zone may severely degrade system performance. How to deal with these uncertainties becomes another direction in the development of ILC.…”
Section: Introductionmentioning
confidence: 99%
“…Since ILC method was proposed by Uchiyama and presented as a formal theory by Arimoto et al, this technique has been the center of interest of many researchers over the last decades [3]. After nearly thirty years' development, ILC has made great progress.…”
Section: Introductionmentioning
confidence: 99%