Adaptive nonlinear control of the czochralski process via integration of second order sliding mode and iterative learning control

Bukhari, Halima Zahra; Aftab, Muhammad Faisal; Winkler, J.; Hovd, Morten

doi:10.1109/ascc.2017.8287609

Cited by 3 publications

(2 citation statements)

References 7 publications

(10 reference statements)

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“…Continuous SMC was created in Reference 6 to alleviate the chattering difficulty by providing an integration approach, although it was not a learning control. LVSC controllers have been used in a variety of applications, including torque‐ripple reduction in permanent magnet synchronous motor, 7 control of Czochralski process in semiconductor industry, 8 electro‐pneumatic, 9 quadrotor UAVs, 10 and so on 11‐14 . provide research publications on the ILC‐SMC combo.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of iterative learning control with different sliding mode algorithms for the slip‐ratio control of an electric vehicle

Denny

Kumar

2023

Intl J Robust & Nonlinear

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Developing a control strategy that can handle model uncertainties, external disturbances, and parameter fluctuations is essential for the desired operation of a nonlinear system. An attempt is made to develop such a control algorithm using the Learning Variable Structure Control technique. The proposed controllers have the advantages of both iterative learning control (ILC) and sliding mode control (SMC) such that they can compensate both structured and unstructured uncertainties. They are made comprised of modified-twisting algorithm and super-twisting algorithm respectively with the ILC technique.In this article, the performance of the two developed controllers is compared to a traditional SMC-based ILC approach. Based on simulation results, the super-twisting algorithm based ILC is found to be superior with reference to speed of convergence and tracking accuracy. This method is used to control the slip-ratio of an electric vehicle as a specific application in this paper.

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Section: Introductionmentioning

confidence: 99%

Performance evaluation of iterative learning control with different sliding mode algorithms for the slip‐ratio control of an electric vehicle

Denny

Kumar

2023

Intl J Robust & Nonlinear

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“…Meanwhile, some scholars have made efforts to overcome the chattering problem in the combined SMC techniques and improved the performance simultaneously. Bukhari et al (2017) combined a second-order sliding mode (SOSM) with ILC scheme to achieve the diameter control in the Czochralski process, which eliminated the chattering phenomenon. The similar concepts were used in the studies by Chen and Chen (2010) and Sun and Li (2016).…”

Section: Introductionmentioning

confidence: 99%

Robust iterative learning control design based on iterative integral sliding mode for nonlinear systems with unrepeatable disturbance

Zhang

2022

Transactions of the Institute of Measurement and Control

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For the repetitive tracking control tasks, the unrepeatable disturbance is an obstruction to learning control schemes. This paper discussed the robust iterative learning control (RILC) design based on the sliding mode control (SMC) technique for a class of nonlinear systems with unrepeatable disturbances. In order to make the tracking error converge to zero in the iteration domain under the sliding mode and eliminate the reaching phase of the SMC, an iterative integral sliding mode (IISM) surface design was proposed. The IISM leads to linear tracking error dynamics in the iteration domain, which guarantees the convergence if the sliding mode parameters meet the given condition. After that, the iterative learning control (ILC) based on the IISM was designed, which drove the sliding mode variable of the closed-loop system to reach the origin with iterations from the initial time instant, despite the effect of the unrepeatable disturbances. The robustness to the unrepeatable disturbance and the fast convergence were achieved. Finally, the proposed IISM method was applied to a one-link robotic manipulator, and the simulation results validated the performance of the proposed control design.

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Model-Free Adaptive Iterative Learning Control Method for the Czochralski Silicon Monocrystalline Batch Process

Ren

Liu

Wan

2021

IEEE Trans. Semicond. Manufact.

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Adaptive nonlinear control of the czochralski process via integration of second order sliding mode and iterative learning control

Cited by 3 publications

References 7 publications

Performance evaluation of iterative learning control with different sliding mode algorithms for the slip‐ratio control of an electric vehicle

Performance evaluation of iterative learning control with different sliding mode algorithms for the slip‐ratio control of an electric vehicle

Robust iterative learning control design based on iterative integral sliding mode for nonlinear systems with unrepeatable disturbance

Model-Free Adaptive Iterative Learning Control Method for the Czochralski Silicon Monocrystalline Batch Process

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