ESO-Based Data Driven Set-Point Learning Control for Nonlinear batch Processes with PD-Type Feedback Control Structure Subject to Nonrepetitive Uncertainties

In this paper, an extended state observer (ESO) based data-driven set-point learning control (DDSPLC) scheme is proposed for nonlinear batch processes configured with an inherent PD-type control loop, so as to actively suppress the adverse effect of nonrepetitive external disturbances and nonidentic...

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Vydané v:	Data Driven Control and Learning Systems Conference (Online) s. 2082 - 2088
Hlavní autori:	Ahmad, Naseem, Hao, Shoulin, Liu, Tao, Gong, Yihui, Zhang, Jiyan, Wang, Haixia, Zhu, Yong
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 17.05.2024
Predmet:	Batch production systems Data-driven set-point learning control Heuristic algorithms Iterative algorithms iterative extended state observer Learning systems nonlinear batch processes nonrepetitive uncertainties Observers PD-type feedback control Process control Uncertainty
ISSN:	2767-9861
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