Creator:

Maniarski, Robert ; Paszke, Wojciech (1975- ) ; Hao, Shoulin ; Tao, Hongfeng

Title:

Robust PD-type iterative learning control design for uncertain batch processes subject to nonrepetitive disturbances

Subject and Keywords:

iterative learning control ; batch processes ; robust control ; nonrepetitive uncertainty

Abstract:

This paper develops PD-type iterative learning control schemes for a class of uncertain batch processes subject to nonrepetitive disturbances. By means of two-dimensional/repetitive setting, the sufficient conditions for batch-to-batch error convergence and $\mathcal{H}_{\infty}$ disturbance attenuation are formulated and analyzed. Subsequently, the procedure for computing the desired control law matrices is formulated in terms of solvability of linear matrix inequalities. ; The proposed control law is able to fulfil the imposed design specifications, i.e., they are suitable for the batch processes with time-varying uncertainties as well as non-repetitive disturbances. An illustrative example is used to validate the proposed control scheme and demonstrates a possible applicability of the developed results.

Description:

artykuł zamieszczony w materiałach konferencyjnych "The 41st Chinese Control Conference - CCC 2022"

Date:

2022

Format:

application/pdf

Language:

eng

License CC BY 4.0:

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Rights:

Biblioteka Uniwersytetu Zielonogórskiego

Sources of funding:

This research was funded in whole or in part by National Science Centre in Poland, grant No. 2020/39/B/ST7/01487.