Robustness of reinforced gradient-type iterative learning control for batch processes with Gaussian noise

doi:10.1016/j.cjche.2015.12.011

Chinese Journal of Chemical Engineering ›› 2016, Vol. 24 ›› Issue (5): 623-629.DOI: 10.1016/j.cjche.2015.12.011

• 第25届中国过程控制会议专栏 • 上一篇下一篇

Robustness of reinforced gradient-type iterative learning control for batch processes with Gaussian noise

Xuan Yang, Xiao'e Ruan

Department of Applied Mathematics, School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, China

收稿日期:2015-02-12 修回日期:2015-07-27 出版日期:2016-05-28 发布日期:2016-06-14
通讯作者: Xiao'e Ruan
基金资助:
Supported by National Natural Science Foundation of China (F010114-60974140, 61273135).

Robustness of reinforced gradient-type iterative learning control for batch processes with Gaussian noise

Xuan Yang, Xiao'e Ruan

Department of Applied Mathematics, School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, China

Received:2015-02-12 Revised:2015-07-27 Online:2016-05-28 Published:2016-06-14
Contact: Xiao'e Ruan
Supported by:
Supported by National Natural Science Foundation of China (F010114-60974140, 61273135).

摘要/Abstract

摘要： In this paper, a reinforced gradient-type iterative learning control profile is proposed by making use of system matrices and a proper learning step to improve the tracking performance of batch processes disturbed by external Gaussian white noise. The robustness is analyzed and the range of the step is specified by means of statistical technique and matrix theory. Compared with the conventional one, the proposed algorithm is more efficient to resist external noise. Numerical simulations of an injection molding process illustrate that the proposed scheme is feasible and effective.

关键词: Batch process, Iterative learning control, Reinforced gradient, Gaussian white noise

Abstract: In this paper, a reinforced gradient-type iterative learning control profile is proposed by making use of system matrices and a proper learning step to improve the tracking performance of batch processes disturbed by external Gaussian white noise. The robustness is analyzed and the range of the step is specified by means of statistical technique and matrix theory. Compared with the conventional one, the proposed algorithm is more efficient to resist external noise. Numerical simulations of an injection molding process illustrate that the proposed scheme is feasible and effective.

Key words: Batch process, Iterative learning control, Reinforced gradient, Gaussian white noise

Xuan Yang, Xiao'e Ruan. Robustness of reinforced gradient-type iterative learning control for batch processes with Gaussian noise[J]. Chinese Journal of Chemical Engineering, 2016, 24(5): 623-629.

Xuan Yang, Xiao'e Ruan. Robustness of reinforced gradient-type iterative learning control for batch processes with Gaussian noise[J]. Chin.J.Chem.Eng., 2016, 24(5): 623-629.

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Robustness of reinforced gradient-type iterative learning control for batch processes with Gaussian noise

Robustness of reinforced gradient-type iterative learning control for batch processes with Gaussian noise

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