Publications

Publications list grouped by Journal/Conference type can be found in Curriculum Vitae.

Students under my close supervision are marked in underline.

Citations can be found in my Google Scholar.

Copyright Notice on the bottom of this page, which must be read and agreed before making any downloads.

Pending

  1. Fengying Dang, Dong Chen, Jun Chen and Zhaojian Li, "Event-Triggered Model Predictive Control with Deep Reinforcement Learning," IEEE Robotics and Automation Letters, (Resubmitted June 2022)

  2. Kaixiang Zhang, Kaian Chen, Zhaojian Li, Jun Chen and Yang Zheng, "Privacy-Preserving Data-Enabled Predictive Leading Cruise Control in Mixed Traffic," IEEE Transactions on Intelligent Transportation Systems, (Submitted May 2022)

  3. Jun Chen, Aman Behal and Chong Li, "Active Cell Balancing by Model Predictive Control for Real Time Electric Vehicles Range Extension," IEEE Transactions on Control Systems Technology, (Submitted September 2021)

  4. Cong Wang, Zhenpo Wang, Lei Zhang, Jun Chen and Dongpu Cao, "Post-Impact Stability Control for Road Vehicles: State-of-the-Art Methodologies and Perspectives," IEEE Transactions on Intelligent Transportation Systems, (Submitted August 2021)

2022

  1. Jun Chen and Junhui Zhao, "Generating Synthetic Wind Speed Scenarios using Artificial Neural Networks for Probabilistic Analysis of Hybrid Energy Systems," International Journal of Modelling, Identification and Control, (Accepted for publication; to appear in 2022)

  2. Ranya Badawi and Jun Chen, "Performance Evaluation of Event-Triggered Model Predictive Control for Boost Converter," IEEE Vehicle Power and Propulsion Conference, Merced, CA, November 1-4, 2022. (Preprint)

  3. Jun Chen and Ratnesh Kumar, "Stochastic Failure Prognosis of Discrete Event Systems," IEEE Transactions on Automatic Control, (Accepted for publication; to appear in October 2022; Preprint)

  4. Ranya Badawi and Jun Chen, "Enhancing Enumeration-Based Model Predictive Control for DC-DC Boost Converter with Event-Triggered Control," European Control Conference, London, UK, July 12-15, 2022. (Download)

  5. Jun Chen, Xiangyu Meng and Zhaojian Li, "Reinforcement Learning-based Event-Triggered Model Predictive Control for Autonomous Vehicle Path Following," American Control Conference, Atlanta, GA, June 8-10, 2022. (Download)

  6. Min Sun, Yiran Hu, David Edwards, Jun Chen, Insu Chang and Steven Moorman, "Active Thermal Management System and Method for Flow Control," U.S. Patent No. US11312208 B2, April 26, 2022. (Download)

  7. Xuan Xie, Guojiang Xiong, Jun Chen and Jing Zhang, "Universal Transparent Artificial Neural Network-Bit ased Fault Section Diagnosis Models for Power Systems," Advanced Theory and Simulations, volume 5, number 4, pages 1-12, April 2022. (Download)

  8. Guojiang Xiong, Xufeng Yuan, Ali Wagdy Mohamed, Jun Chen and Jing Zhang, "Improved Binary Gaining-sharing Knowledge based Algorithm with Mutation for Fault Section Location in Distribution Networks," Journal of Computational Design and Engineering, volume 9, number 2, pages 393-405, April 2022. (Download)

  9. Shan Huang and Jun Chen, "Event-triggered Model Predictive Control for Autonomous Vehicle with Rear Steering," SAE World Congress, Detroit, MI, April 5-7, 2022. (Download, Slides)

2021

  1. Jun Chen, Aman Behal and Chong Li, "Active Cell Balancing by Model Predictive Control for Real Time Range Extension," IEEE Conference on Decision and Control, Austin, TX, December 13-15, 2021. (Download)

  2. Jun Chen, Ruixing Long and Yiran Hu, "Method for Increasing Control Performance of Model Predictive Control Cost Functions," U.S. Patent No. US11192561 B2, December 7, 2021. (Download)

  3. Jun Chen and Zonggen Yi, "Comparison of Event-Triggered Model Predictive Control for Autonomous Vehicle Path Tracking," IEEE Conference on Control Technology and Applications, San Diego, CA, August 8-11, 2021. (Download)

  4. Yiran Hu, David Edwards, Michael Paratore Jr, Min Sun, Jun Chen, Eugene Gonze, Sergio Quelhas, "Method and Apparatus for Control of Propulsion System Warmup Based on Engine Wall Temperature," U.S. Patent No. 11078825 B2, August 3, 2021. (Download)

  5. Jun Chen and Ramesh S, "Model-based Validation of Diagnostic Software with Application in Automotive Systems," IET Cyber-Systems and Robotics, volume 3, number 2, pages 140–149, June 2021. (Download)

  6. Jun Chen and Junhui Zhao, "Synthetic Wind Speed Scenarios Generation using Artificial Neural Networks for Probabilistic Analysis of Hybrid Energy Systems," IEEE International Symposium on Industrial Electronics, Kyoto, Japan, June 20-23, 2021. (Download)

  7. Jun Chen, David Edwards, Yiran Hu, Min Sun, Adam Heinzen and Michael Smith, "Method and System for Determining Thermal State," U.S. Patent No. 10995688 B2, May 4, 2021. (Download)

  8. Jun Chen, Man Liang and Xu Ma, "Probabilistic Analysis of Electric Vehicle Energy Consumption Using MPC Speed Control and Nonlinear Battery Model," IEEE Green Technologies Conference, Denver, CO, April 7-9, 2021. (Download)

  9. Jun Chen, Zhaojian Li and Xiang Yin, "Optimization of Energy Storage Size and Operation for Renewable-EV Hybrid Energy Systems," IEEE Green Technologies Conference, Denver, CO, April 7-9, 2021. (Download)

2020

  1. Jun Chen, "Extended Kalman Filter Steady Gain Scheduling Using k-means Clustering," International Journal of Modelling, Identification and Control, volume 34, number 2, pages 158–162, February 2020. (Download)

2019

  1. Xiang Yin, Jun Chen, Zhaojian Li and Shaoyuan Li, "Robust Fault Diagnosis of Stochastic Discrete Event Systems," IEEE Transactions on Automatic Control, volume 64, number 10, pages 4237–4244, October 2019. (Download)

2018

  1. Jun Chen, Qin Wang, Jianming Lian and Wanning Li, "Guest editorial: advances in control and decision for power and energy systems," Journal of Control and Decision, volume 5, number 2, pages 115-116, February 2018.

  2. Jun Chen, Christoforos Keroglou, Christoforos N. Hadjicostis and Ratnesh Kumar, "Revised Test for Stochastic Diagnosability of Discrete-Event Systems," IEEE Transactions on Automation Science and Engineering, volume 15, number 1, pages 404-408, January 2018. (Download)

2017

  1. Jun Chen, Peter Molnar and Aman Behal, "Identification of a Stochastic Resonate-and-Fire Neuronal Model via Nonlinear Least Squares and Maximum Likelihood Estimation," International Journal of Modelling, Identification and Control, volume 28, number 3, pages 221-231, October 2017. (Download)

  2. Aaron S. Epiney, Andrea Alfonsi, Cristian Rabiti and Jun Chen, "Economic Assessment of Nuclear Hybrid Energy Systems: Optimization using RAVEN," ANS Summer Meeting, San Francisco, CA, June 11-15, 2017. (Download)

  3. Jun Chen, Jong S. Kim and Cristian Rabiti, "Probabilistic Analysis of Hybrid Energy Systems Using Synthetic Renewable and Load Data," American Control Conference, Seattle, WA, May 24-26, 2017. (Download)

  4. Cristian Rabiti, Andrea Alfonsi, Joshua Cogliati, Diego Mandelli, Robert Kinoshita, Sonat Sen, Congjian Wang and Jun Chen, "RAVEN User Manual," INL/EXT-15-34123 Revision 5, ID: Idaho National Laboratory, March 2017. (Download)

  5. Jun Chen and Cristian Rabiti, "Synthetic Wind Speed Scenarios Generation for Probabilistic Analysis of Hybrid Energy Systems," Energy, volume 120, pages 507-517, February 2017. (Download)

  6. Jun Chen, Mariam Ibrahim and Ratnesh Kumar, "Quantification of Secrecy in Partially Observed Stochastic Discrete Event Systems," IEEE Transactions on Automation Science and Engineering, volume 14, number 1, pages 185-195, January 2017. (Download)

2016

  1. Jong S. Kim, Jun Chen and Humberto E. Garcia, "Modeling, Control, and Dynamic Performance Analysis of a Reverse Osmosis Desalination Plant Integrated within Hybrid Energy Systems," Energy, volume 112, pages 52-66, October 2016. (Download)

  2. Jun Chen and Humberto E. Garcia, "Economic Optimization of Operations for Hybrid Energy Systems under Variable Markets," Applied Energy, volume 177, pages 11-24, September 2016. (Download)

  3. Joshua J. Cogliati, Jun Chen, Japan K. Patel, Diego Mandelli, Daniel P. Maljovec, Andrea Alfonsi, Paul W. Talbot, Congjian Wang and Cristian Rabiti, "Time Dependent Data Mining in RAVEN," INL/EXT-16-39860, Idaho Falls, ID: Idaho National Laboratory, September 2016. (Download)

  4. Aaron Epiney, Jun Chen and Cristian Rabiti, "Status on the Development of a Modeling and Simulation Framework for the Economic Assessment of Nuclear Hybrid Energy Systems (FY 16)," INL/EXT-16-39832, Idaho Falls, ID: Idaho National Laboratory, September 2016.

  5. Jun Chen, Humberto E. Garcia, Jong S. Kim and Shannon M. Bragg-Sitton, "Operations Optimization of Nuclear Hybrid Energy Systems," Nuclear Technology, volume 195, number 2, pages 143-156, August 2016. (Download)

  6. Humberto E. Garcia, Jun Chen, Jong S. Kim, Richard B. Villim, William R. Binder, Shannon M. Bragg-Sitton, Richard D. Boardman, Michael G. McKellar and Christiaan J. J. Paredis, "Dynamic Performance Analysis of Two Regional Nuclear Hybrid Energy Systems," Energy, volume 107, pages 234-258, July 2016. (Download)

  7. Jun Chen and Humberto E. Garcia, "Operations Optimization of Hybrid Energy Systems under Variable Markets," American Control Conference, Boston, MA, July 6-8, 2016. (Download)

  8. Mariam Ibrahim, Jun Chen and Ratnesh Kumar, "Quantification of Distributed Secrecy Loss in Stochastic Discrete Event Systems under Bounded-Delay Communications," IFAC/IEEE International Workshop on Discrete Event Systems, Xi'an, China, May 30-June 1, 2016. (Download)

  9. Mariam Ibrahim, Jun Chen and Ratnesh Kumar, "A Resiliency Measure for Electrical Power Systems," IFAC/IEEE International Workshop on Discrete Event Systems, Xi'an, China, May 30-June 1, 2016. (Download)

  10. Mariam Ibrahim, Jun Chen and Ratnesh Kumar, "Quantification of Centralized/Distributed Secrecy in Stochastic Discrete Event Systems," in Recent Advances in Systems Safety and Security, Editors: Emil Pricop and Grigore Stamatescu, Springer, May 2016, ISBN: 978-3-319-32523-1. (Download)

  11. Shannon M. Bragg-Sitton, Richard D. Boardman, Cristian Rabiti, Jong S. Kim, Michael G. McKellar, Piyush Sabharwall, Jun Chen, M. Sacit Cetiner, T. Jay Harrison and A. Lou Qualls, "Nuclear-Renewable Hybrid Energy Systems: 2016 Technology Development Program Plan," INL/MIS-16-38165, Idaho Falls, ID: Idaho National Laboratory, March 2016. (Download)

2015

  1. Shannon M. Bragg-Sitton, Richard D. Boardman, Cristian Rabiti, Jong S. Kim, Michael G. McKellar, Piyush Sabharwall, Jun Chen, Mark Ruth, M. Sacit Cetiner, T. Jay Harrison and A. Lou Qualls, "Nuclear-Renewable Hybrid Energy Systems 2016 Technology Development Roadmap (DRAFT)," INL/EXT-15-37446, Idaho Falls, ID: Idaho National Laboratory, December 2015.

  2. Jun Chen and Ratnesh Kumar, "Fault Detection of Discrete-Time Stochastic Systems Subject to Temporal Logic Correctness Requirement," IEEE Transactions on Automation Science and Engineering, volume 12, number 4, pages 1369-1379, October 2015. (Best Paper Award, Download)

  3. Jun Chen and Ratnesh Kumar, "Stochastic Failure Prognosability of Discrete Event Systems," IEEE Transactions on Automatic Control, volume 60, number 6, pages 1570-1581, June 2015. (Download)

  4. Jun Chen and Ratnesh Kumar, "Failure Detection Framework for Stochastic Discrete Event Systems with Guaranteed Error Bounds," IEEE Transactions on Automatic Control, volume 60, number 6, pages 1542-1553, June 2015. (Download)

  5. Mariam Ibrahim, Jun Chen and Ratnesh Kumar, "An Information Theoretic Measure of Secrecy Loss in Stochastic Discrete Event Systems," International Conference on Electronics, Computers and Artificial Intelligence - International Workshop on Systems, Safety and Security, Bucharest, Romania, June 25-27, 2015. (Download)

  6. Humberto E. Garcia, Jun Chen, Jong S. Kim, Michael G. McKellar, Wesley R. Deason, Richard B. Villim, Shannon M. Bragg-Sitton and Richard Boardman, "Nuclear Hybrid Energy Systems - Regional Studies: West Texas & Northeastern Arizona," INL/EXT-15-34503, Idaho Falls, ID: Idaho National Laboratory, April 2015. (Download)

2014

  1. Jun Chen and Ramesh S, "Model-based Validation of Diagnostic Specification," Electrical & Controls Systems Lab, General Motors Research & Development Center, Warren, MI, July 2014.

  2. Jun Chen and Ratnesh Kumar, "Failure Prognosability of Stochastic Discrete Event Systems," American Control Conference, Portland, OR, June 4-6, 2014. (Download)

  3. Jun Chen and Ratnesh Kumar, "Pattern Mining for Predicting Critical Events from Sequential Event Data Log," IFAC/IEEE International Workshop on Discrete Event Systems, Paris-Cachan, France, May 14-16, 2014. (Download)

  4. Jun Chen and Ratnesh Kumar, "Failure Diagnosis of Discrete-Time Stochastic Systems Subject to Temporal Logic Correctness Requirement," IEEE International Conference on Networking, Sensing and Control, Miami, FL, April 7-9, 2014. (Download)

  5. Mariam Ibrahim, Jun Chen and Ratnesh Kumar, "Secrecy in Stochastic Discrete Event Systems," IEEE International Conference on Networking, Sensing and Control, Miami, FL, April 7-9, 2014. (Download)

2013

  1. Jun Chen and Ratnesh Kumar, "Polynomial Test for Stochastic Diagnosability of Discrete Event Systems," IEEE Transactions on Automation Science and Engineering, volume 10, number 4, pages 969-979, October 2013.

  2. Jun Chen and Ratnesh Kumar, "Online Failure Diagnosis of Stochastic Discrete Event Systems," IEEE Multi-Conference on Systems and Control - IEEE Conference on Computer Aided Control System Design, Hyderabad, India, August 28-30, 2013. (Download)

  3. Jun Chen and Ratnesh Kumar, "Decentralized Failure Diagnosis of Stochastic Discrete Event Systems," IEEE Conference on Automation Science and Engineering, Madison, WI, August 17-21, 2013.

2012

  1. Jun Chen and Ratnesh Kumar, "Polynomial Test for Stochastic Diagnosability of Discrete Event Systems," IEEE Conference on Automation Science and Engineering, Seoul, Korea, August 20-24, 2012.

  2. Lingfei Zhi, Jun Chen, Peter Molnar and Aman Behal, "Weighted Least-Squares Approach for Identification of a Reduced-Order Adaptive Neuronal Model," IEEE Transactions on Neural Networks and Learning Systems, volume 23, number 5, pages 834-840, May 2012. (Download)

2011

  1. Jun Chen, Jose Suarez, Peter Molnar and Aman Behal, "Maximum Likelihood Parameter Estimation in a Stochastic Resonate-and-Fire Neuronal Model," IEEE International Conference on Computational Advances in Bio and medical Sciences (ICCABS), Orlando, FL, February 3-5, 2011. (Download)

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