Application of robust iterative learning algorithm in motion control system

Lin, Ming-Tzong; Yen, Chung-Liang; Tsai, Meng-Shiun; Yau, Hong-Tzong

doi:10.1016/j.mechatronics.2013.04.006

Cited by 24 publications

(14 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…c2) The number of learning iteration j is larger than a given value and the relative ratio of synchronous error ε rel is greater than a given value, that is, j ≥ J 0 and ε rel ¼ ε rms;j ε rms;jÀ1 ≥ e rr (22) Criterion c1 is obvious since in general the ultimate goal is to reduce the error without ILC by a certain amount of percentage after learning. c2) The number of learning iteration j is larger than a given value and the relative ratio of synchronous error ε rel is greater than a given value, that is, j ≥ J 0 and ε rel ¼ ε rms;j ε rms;jÀ1 ≥ e rr (22) Criterion c1 is obvious since in general the ultimate goal is to reduce the error without ILC by a certain amount of percentage after learning.…”

Section: L4) Perform the Systematic Algorithm Proposed Inmentioning

confidence: 99%

“…It can also be categorized into time domain [17] or frequency domain [18], depending on the analysis and implementation of the ILC algorithm. Based on the output errors in the previous operation cycle, the former is used to modify the control inputs [19], and the latter to modify the commands [20][21][22]. Based on the output errors in the previous operation cycle, the former is used to modify the control inputs [19], and the latter to modify the commands [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Performance Enhancement for Rigid Tapping by Iterative Learning Control

Chen

Wen

Zhao

2018

Asian Journal of Control

View full text Add to dashboard Cite

In this study, an iterative learning control (ILC) algorithm is proposed to improve synchronous errors in rigid tapping. In rigid tapping, the displacements of the z-axis and spindle must be kept synchronous to prevent damage. Using learning control provides better commands for both the z-axis and spindle dynamics, improving the synchronicity of the output responses of the z-axis and spindle. The proposed ILC makes use of synchronous errors in the previous cycle of tapping to modify the current position commands of both the z-axis and spindle. A systematic algorithm is proposed for the computation of learning gains that guarantee the monotonic convergence of synchronous errors. A systematic procedure of applying ILC to rigid tapping is also proposed, where the ideas of effective learning gains and stop learning criteria are discussed. Experimental results on a tapping machine verify the effectiveness of the proposed ILC algorithm.

show abstract

Section: L4) Perform the Systematic Algorithm Proposed Inmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance Enhancement for Rigid Tapping by Iterative Learning Control

Chen

Wen

Zhao

2018

Asian Journal of Control

View full text Add to dashboard Cite

show abstract

“…The objective of ILC is to determine a control input iteratively, resulting in plant's ability to track the given reference signal or the output trajectory over a fixed time interval. Owing to its simplicity and effectiveness, ILC has been found to be a good alternative in many areas and applications, see recent surveys for detailed results [7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Fractional order nonlinear systems with delay in iterative learning control

Wei

2015

Applied Mathematics and Computation

View full text Add to dashboard Cite

“…However, when there is periodic disturbance, the approaches proposed in [1] and [2] may fail to attain satisfactory tracking performance. In order to overcome this difficulty, this paper proposes a control structure that employs an Iterative Learning Control (ILC) scheme [3,4] to suppress periodic external disturbance. ILC has been shown to be very effective in dealing with systems with periodic disturbance.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, a command-based ILC has been developed in [3] to compensate for friction, disturbance, and modeling error. Tsai et al further developed a robust ILC to improve positioning accuracy of a bi-axial motion control system [4].…”

Section: Introductionmentioning

confidence: 99%

Contour following control of two-axis servomechanism using CMAC and ILC

Kuo

Chen

Cheng

2014

2014 CACS International Automatic Control Conference (CACS 2014)

View full text Add to dashboard Cite

In addition to positioning control, contour following control is also an important application of two-axis servomechanisms such as X-Y tables. Therefore, the reduction of contour following error so as to improve contour following accuracy is one of the important research topics for two-axis servomechanisms. Generally, the assessment of contour following accuracy is based on two error indices tracking error and contour error. Although the reduction of tracking error can lead to the improvement of contour following accuracy, many previous studies suggest that contour error is a more crucial indicator than tracking error in contour following applications. As a result, this paper aims at developing a control scheme for contour error reduction so as to improve contour following accuracy. The proposed control scheme consists of a PI type feedback controller, a Cerebellar Model Articulation Control (CMAC) algorithm and an Iterative learning Control (ILC) scheme. In particular, the CMAC is combined with the ILC to compensate for the adverse effects due to external disturbance and nonlinear phenomenon. Experimental results verify the effectiveness of the proposed contour following control scheme.

show abstract

Application of robust iterative learning algorithm in motion control system

Cited by 24 publications

References 26 publications

Performance Enhancement for Rigid Tapping by Iterative Learning Control

Performance Enhancement for Rigid Tapping by Iterative Learning Control

Fractional order nonlinear systems with delay in iterative learning control

Contour following control of two-axis servomechanism using CMAC and ILC

Contact Info

Product

Resources

About