Fuzzy System-Based Adaptive Iterative Learning Control for Nonlinear Plants With Initial State Errors

Chien, Chiang‐Ju; Hsu, Chun-Te; Yao, Chia-Yu

doi:10.1109/tfuzz.2004.834806

Cited by 106 publications

(47 citation statements)

References 19 publications

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“…The forms of learning function covered above form the majority of the prior art but there are many other forms that have been investigated including, Fuzzy ILC [99] …”

Section: Other Learning Functionsmentioning

confidence: 99%

Control of a fast switching valve for digital hydraulics

Sell¹

2013

Linköping Electronic Conference Proceedings

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“…The forms of learning function covered above form the majority of the prior art but there are many other forms that have been investigated including, Fuzzy ILC [99] …”

Section: Other Learning Functionsmentioning

confidence: 99%

Control of a fast switching valve for digital hydraulics

Sell¹

2013

Linköping Electronic Conference Proceedings

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“…But zero error tracking performance cannot be achieved by robust control, otherwise, the system Will be caused chattering phenomenon. Repetitive control technique is used for periodic operation of the controlled object [5][6], when there is repeatitive periodic interference with timevarying delay system, repetitive control can be very good to eliminate the tracking error, the repetitive controller in the paper can not only improve the tracking accuracy of the system, but also to improve the robustness of the system, which can verify that the controller has practical value in engineering.…”

Section: Introductionmentioning

confidence: 99%

Study on Repetitive Control of Hydraulic Servo Systems with Uncertain Time-Varying and Time-Delay

Ji-Qiong

Guang-yi

2015

2015 Seventh International Conference on Measuring Technology and Mechatronics Automation

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The hydraulic servo system with timevarying and time-delay uncertain has been used as the research object, the repetitive control method has been proposed, the repetitive controller has been designed, and the simulation has carried on, so the simulation results have shown that the system output can track the given cycle reference signals very fast, the tracking error can converge to zero asymptotically very fast, which has illustrated fully that not only repetitive control can improve the system tracking accuracy, but also can improve the robustness of the system.

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“…It should be noted that the robust convergence in the presence of arbitrary but bounded repositioning errors can be achieved by the Lyapunov-like approach. A time-varying boundary layer was introduced for the controller design in [20], and the tracking error was shown to converge to the boundary layer region. In [21], the initial rectifying action was shown to be effective to realize the goal of complete tracking over a pre-specified interval, except for a short segment from the initial position.…”

Section: Introductionmentioning

confidence: 99%

Repetitive learning control of nonlinear systems over finite intervals

Sun

Wang

Chen

2010

Sci. China Inf. Sci.

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Iterative learning control requires initial repositioning, while the time functions to be learned should be of periodicity in repetitive control. However, there are cases in practice where the time-varying unknowns are not periodic but repetitive, and repetitive learning control is applicable with avoidance of initial repositioning. In this paper, repetitive learning control designs are presented for a broader class of nonlinear systems over finite intervals. The Freeman formula is modified and used for stabilization of the nominal nonlinear time-varying system undertaken. The global stability of the learning system and asymptotic convergence of the tracking error are established through analysis of both partially and fully saturated learning algorithms, respectively. The repetitive learning control method is theoretically shown to be effective in dealing with time-varying parametric uncertainties. CitationSun M X, Wang D W, Chen P N. Repetitive learning control of nonlinear systems over finite intervals.

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Fuzzy System-Based Adaptive Iterative Learning Control for Nonlinear Plants With Initial State Errors

Cited by 106 publications

References 19 publications

Control of a fast switching valve for digital hydraulics

Control of a fast switching valve for digital hydraulics

Study on Repetitive Control of Hydraulic Servo Systems with Uncertain Time-Varying and Time-Delay

Repetitive learning control of nonlinear systems over finite intervals

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