Yi Yang
Zhejiang University
55 Papers
168 Citations
Yi Yang is an academic researcher from Zhejiang University. The author has contributed to research in topics: Iterative learning control & Batch processing. The author has an hindex of 16, co-authored 55 publications. Previous affiliations of Yi Yang include Hong Kong University of Science and Technology.
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Papers
PCA-Based Modeling and On-line Monitoring Strategy for Uneven-Length Batch Processes
TL;DR: The stage-based sub-PCA modeling method originally proposed by the authors is extended to the monitoring of batch processes with durations of uneven lengths, to enhance process understanding and to provide stage-division information necessary for the development of PCA monitoring models.
114
Adaptive control of the filling velocity of thermoplastics injection molding
Yi Yang,Furong Gao +1 more
TL;DR: In this article, a generalized predictive control (GPC) based adaptive controller was designed to make the controller more robust to model structure mismatch, which has inherently good set-point tracking performance and excellent tolerance to model structural mismatch.
106
Injection molding product weight: Online prediction and control based on a nonlinear principal component regression model
Yi Yang,Furong Gao +1 more
TL;DR: In this paper, an online weight prediction model has been developed, with the process variable trajectories as the inputs, using a principal component regression (PCR) model, and a nonlinear enhancement has been made to improve the prediction accuracy of the PCR weight model.
85
Cycle-to-cycle and within-cycle adaptive control of nozzle pressure during packing-holding for thermoplastic injection molding
Yi Yang,Furong Gao +1 more
TL;DR: In this paper, an adaptive self-tuning controller was designed and implemented to control the packing phase of injection molded parts, and several improvements-an anti-windup estimate, an adaptive feedforward, and cycle-to-cycle adaptation-were incorporated to produce excellent packing pressure control results.
64
Multirate dynamic inferential modeling for multivariable processes
TL;DR: In this paper, a PLS-based multirate dynamic modeling is proposed for quality prediction at a faster rate for multivariable processes with different sampling rates between the process and quality variables.
62