Journal ArticleDOI
A batch-to-batch iterative optimal control strategy based on recurrent neural network models
Zhihua Xiong,Jie Zhang +1 more
TLDR
A batch-to-batch model-based iterative optimal control strategy for batch processes is proposed, where a quadratic objective function is introduced to track the desired qualities at the end-point of a batch.About:
This article is published in Journal of Process Control.The article was published on 2005-02-01. It has received 149 citations till now. The article focuses on the topics: Batch processing & Iterative learning control.read more
Citations
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Journal ArticleDOI
Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network
TL;DR: Comparisons with other existing methods demonstrate that the SR-RBF-NMPC can achieve a considerably better model fitting for WWTP and a better control performance for DO concentration.
Journal ArticleDOI
Data-driven optimal terminal iterative learning control
TL;DR: Rigorous analysis and convergence proof are developed with sufficient conditions for the terminal ILC design and the results are developed for both linear and nonlinear discrete-time systems.
Journal ArticleDOI
Just-in-time kernel learning with adaptive parameter selection for soft sensor modeling of batch processes
TL;DR: An efficient nonlinear just-in-time learning (JITL) soft sensor method for online modeling of batch processes with uneven operating durations and the superiority of the proposed soft sensor approach is demonstrated by predicting the concentrations of the active biomas.
Journal ArticleDOI
Neural network applications in polymerization processes
TL;DR: A brief tutorial on simple and practical procedures that can help in selecting and training neural networks and addresses complex cases where the application of neural networks has been successful in the field of polymerization.
Journal ArticleDOI
Recurrent Neural Network-based Model Predictive Control for Continuous Pharmaceutical Manufacturing
TL;DR: RNNs were shown to be especially well-suited for modelling dynamical systems due to their mathematical structure, and their use in system identification has enabled satisfactory closed-loop performance for MPC of a complex reaction in a single continuous-stirred tank reactor (CSTR) for pharmaceutical manufacturing.
References
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Journal ArticleDOI
Approximation by superpositions of a sigmoidal function
TL;DR: It is demonstrated that finite linear combinations of compositions of a fixed, univariate function and a set of affine functionals can uniformly approximate any continuous function ofn real variables with support in the unit hypercube.
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Backpropagation through time: what it does and how to do it
TL;DR: This paper first reviews basic backpropagation, a simple method which is now being widely used in areas like pattern recognition and fault diagnosis, and describes further extensions of this method, to deal with systems other than neural networks, systems involving simultaneous equations or true recurrent networks, and other practical issues which arise with this method.
Journal ArticleDOI
Nonlinear black-box modeling in system identification: a unified overview
Jonas Sjöberg,Qinghua Zhang,Lennart Ljung,Albert Benveniste,Bernard Delyon,Pierre-Yves Glorennec,Håkan Hjalmarsson,Anatoli Juditsky +7 more
TL;DR: What are the common features in the different approaches, the choices that have to be made and what considerations are relevant for a successful system-identification application of these techniques are described, from a user's perspective.
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Neural networks for control systems: a survey
TL;DR: In this paper, the authors focus on the promise of artificial neural networks in the realm of modelling, identification and control of nonlinear systems and explore the links between the fields of control science and neural networks.
Journal ArticleDOI
Process monitoring and diagnosis by multiblock PLS methods
TL;DR: More detailed diagnostic methods based on interrogating the underlying PCA /PLS models are developed, which show those process variables which are the main contributors to any deviations that have occurred, thereby allowing one to diagnose the cause of the event more easily.