Terminal constrained robust hybrid iterative learning model predictive control for complex time-delayed batch processes-Reference-Cited by-同舟云学术

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Terminal constrained robust hybrid iterative learning model predictive control for complex time-delayed batch processes

Published:2023-02 Issue: Volume:47 Page:101276
ISSN:1751-570X
Container-title:Nonlinear Analysis: Hybrid Systems
language:en
Short-container-title:Nonlinear Analysis: Hybrid Systems

Author:

Wang Limin,Zhang Wangxi,Zhang Qiyuan,Shi Huiyuan,Zhang Ridong,Gao Furong

Funder

Natural Science Foundation of Hainan Province

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Publisher

Elsevier BV

Subject

Computer Science Applications,Analysis,Control and Systems Engineering

Reference34 articles.

1. Batch process control-overview and outlook;Lu;Acta. Autom. Sinica,2017

2. Iterative Learning Stabilization and Fault-Tolerant Control for Batch Processes;Wang,2020

3. Control performance assessment for ILC-controlled batch processes in a 2D system framework;Wang;IEEE Trans. Syst. Man. Cybern. Syst.,2017

4. Sustainable batch process retrofit design under uncertainty - An integrated methodology;Pinto-Varela;Comput. Chem. Eng.,2016

5. Robust batch-to-batch optimization in the presence of model-plant mismatch and input uncertainty;Hille;Aiche J.,2017

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4. An integrated tube robust iterative learning model predictive control strategy based on dynamic partial least squares algorithm for batch processes;The Canadian Journal of Chemical Engineering;2024-04-17

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