Lee Rippon

Lee Rippon

Interested in process control and artificial intelligence. Particularly, in ML algorithms for APC and FDD in process systems applications.

Publications

Representation Learning and Predictive Classification: Application with an Electric Arc Furnace

Published in Computers & Chemical Engineering, 2021

A comprehensive representation learning and predictive classification framework is presented for development of the inferential sensor from large quantities of historical industrial process data.

Recommended citation: Rippon, L. D., Yousef, I., Hosseini, B., Bouchoucha, A., Beaulieu, J. F., Prevost, C., Ruel, M., Shah, S. L., & Gopaluni, R. B. (2021). "Representation learning and predictive classification: Application with an electric arc furnace." Computers & Chemical Engineering. https://www.sciencedirect.com/science/article/abs/pii/S009813542100082X

Closed-loop model parameter identification techniques for industrial model-based process controllers

Published in Patent No.: US 10,761,522 B2, 2020

Patent granted: two-stage closed-loop identification strategy that leverages ARX and output-error models.

Recommended citation: Lu, Q., Rippon, L. D., Gopaluni, R. B., Forbes, M. G., Loewen, P. D., Backström, J., & Dumont, G. A. (2020). "Closed-loop model parameter identification techniques for industrial model-based process controllers." U.S. Patent. No.: US 10,761,522 B2. https://patentimages.storage.googleapis.com/f2/80/e4/202e0d00ddd3f5/US10761522.pdf

Process analytics and machine learning to predict arc losss in an electric arc furnace

Published in 59th Conference of Metallurgists, 2020

An inferential sensor is developed to warn operators of a high risk of impending arc loss so that they can take corrective actions and avoid the process fault.

Recommended citation: Rippon, L. D., Yousef, I., Hosseini, B., Beaulieu, J. F., Prevost, C., Shah, S. L., & Gopaluni, R. B. (2020). "Process analytics and machine learning to predict arc losss in an electric arc furnace." 59th Conference of Metallurgists 2020. https://dais.chbe.ubc.ca/assets/preprints/2020C5_Rippon_COM.pdf

Machine direction adaptive control on a paper machine

Published in Industrial & Engineering Chemistry Research, 2019

This work addresses the sheet profile estimation problem with a novel compressive sensing strategy and the adaptive control problem with a comprehensive monitoring, optimal input design and system identification strategy.

Recommended citation: Rippon, L. D., Lu, Q., Forbes, M. G., Gopaluni, R. B., Loewen, P. D., & Backström, J. U. (2019). "Machine direction adaptive control on a paper machine." Industrial & Engineering Chemistry Research. 58(26), 11452-11473. https://pubs.acs.org/doi/abs/10.1021/acs.iecr.8b06067

Data-driven dynamic modeling and online monitoring for multiphase and multimode batch processes with uneven batch durations

Published in Industrial & Engineering Chemistry Research, 2019

A modeling and monitoring strategy applied to a multiphase and multimode batch penicillin fermentation processes that involves linear dynamics, k-means clustering and expectation maximization.

Recommended citation: Wang, K., Rippon, L., Chen, J., Song, Z., & Gopaluni, R. B. (2019). "Data-driven dynamic modeling and online monitoring for multiphase and multimode batch processes with uneven batch durations." Industrial & Engineering Chemistry Research. 58(30), 13628-13641. https://pubs.acs.org/doi/abs/10.1021/acs.iecr.9b00290

Pattern and knowledge extraction using process data analytics: A tutorial

Published in ADCHEM Shenyang, IFAC-PapersOnLine, 2018

This tutorial was accompanied by a conference workshop at ADCHEM in China and together they were designed to familiarize control engineers with advances in statistical machine learning.

Recommended citation: Tsai, Y., Lu, Q., Rippon, L., Lim, S., Tulsyan, A., & Gopaluni, B. (2018). "Pattern and knowledge extraction using process data analytics: A tutorial." IFAC-PapersOnLine. 51(18), pp. 13-18. https://www.sciencedirect.com/science/article/pii/S240589631831913X

Noncausal modeling and closed-loop optimal input design for cross-directional processes of paper machines

Published in American Control Conference (ACC) Seattle, IEEE, 2017

Optimal inputs for closed-loop identification are designed with a noncausal transfer function model.

Recommended citation: Lu, Q.,Rippon, L. D., Gopaluni, R. B., Forbes, M. G., Loewen, P. D., Backström, J., & Dumont, G. A. (2017). "Noncausal modeling and closed-loop optimal input design for cross-directional processes of paper machines." American Control Conference (ACC). (pp. 2837-2842). IEEE. https://ieeexplore.ieee.org/abstract/document/7963381

Sheet profile estimation and machine direction adaptive control

Published in University of British Columbia, Vancouver, 2017

A comparative analysis of MD-CD separation strategies is presented along with a comprehensive adaptive control framework for paper machines.

Recommended citation: Rippon, L. D. (2017). "Sheet profile estimation and machine direction adaptive control." University of British Columbia, Vancouver. MASc dissertation. https://open.library.ubc.ca/cIRcle/collections/ubctheses/24/items/1.0347279

Cross-directional controller performance monitoring for paper machines

Published in American Control Conference (ACC) Chicago, IEEE, 2015

Development of a performance index that monitors a paper machine control system.

Recommended citation: Lu, Q., Rippon, L. D., Gopaluni, R. B., Forbes, M. G., Loewen, P. D., Backstrom, J., & Dumont, G. A. (2015). "Cross-directional controller performance monitoring for paper machines." American Control Conference (ACC). (pp. 4970-4975). IEEE. https://ieeexplore.ieee.org/abstract/document/7172113

Moving-horizon predictive input design for closed-loop identification

Published in ADCHEM Whistler, IFAC-PapersOnLine, 2015

Designing optimal excitation signals for closed-loop system identification.

Recommended citation: Yousefi, M., Rippon, L. D., Forbes, M. G., Gopaluni, R. B., Loewen, P. D., Dumont, G. A., & Backstrom, J. (2015). "Moving-horizon predictive input design for closed-loop identification." IFAC-PapersOnLine. 48(8), 135-140. https://www.sciencedirect.com/science/article/pii/S240589631501037X