NSERC Industrial Research Chair in the Control of Oil Sands Processes

2017

  1. M. Fang,  H. Kodamana, B. Huang*, A Novel Approach to Process Operating Mode Diagnosis Using Conditional Random Fields in the Presence of Missing Data, Computers & Chemical Engineering, accepted Dec. 2017.
  2. J. Ma*, O. Wu, B. Huang, F. Ding, Expectation maximization estimation for a class of input nonlinear state space systems by using the Kalman smoother, Signal Processing, accepted Dec. 2017.
  3. L. Fan, H. Kodamana, B. Huang*, Identification of Robust Probabilistic Slow Feature Regression Model for Process Data Contaminated with Outliers, Chemometrics and Intelligent Laboratory Systems, accepted Dec. 2017.
  4. Y. Ma, B. Huang*, Extracting Dynamic Features with Switching Models for Process Data Analytics and Application in Soft Sensing, AIChE J., accepted Dec. 2017.
  5. C. Zhao, B. Huang*, A Full-condition Monitoring Method for Nonstationary Dynamic Processes with Cointegration and Slow Feature Analysis, AIChE J., accepted Dec. 2017.
  6. X. Hong, Y. Ding, L. Ren, L. Chen, B. Huang*, A Weighted Heteroscedastic Gaussian Process Modelling via Particle Swarm Optimization, Chemometrics and Intelligent Laboratory Systems, accepted Nov. 2017.
  7. H. Kodamana, R. Raveendran, B. Huang*, Mixtures of probabilistic PCA with common structure latent bases for process monitoring, IEEE Transactions on Control Systems Technology, accepted Nov. 2017.
  8. H. Mei, Z. Wang, B.  Huang*, Molecular-based Bayesian regression model of petroleum fractions, Industrial & Engineering Chemistry Research, accepted Nov 2017.
  9. H. Alighardashi, N. Magbool Jan, B. Huang*, Expectation Maximization Approach for Simultaneous Gross Error Detection and Data Reconciliation Using Gaussian Mixture Distribution, Industrial & Engineering Chemistry Research, accepted Nov 2017.
  10. Z. Ge*, Z. Song, S.X. Ding, B. Huang, Data Mining and Analytics in the Process Industry: the Role of Machine Learning, IEEE Access, Volume 5, 20590 - 20616, September 2017.
  11. J. Ma, B. Huang*, F. Ding, Iterative Identification of Hammerstein Parameter Varying Systems with Parameter Uncertainties Based on Variational Bayesian Approach, IEEE Transactions on Systems, Man and Cybernetics: Systems, accepted Sept 2017.
  12. Y. Yuan, Z. Li*, B. Huang, Nonlinear Robust Optimization for Process Design, AIChE J., September 2017, 64, 481-494
  13. G. Wang, K. Velswamy, B. Huang*, A Long-Short Term Memory Recurrent Neural Network Based Reinforcement Learning Controller for Office Heating Ventilation and Air Conditioning Systems, Processes, Processes 2017, 5, 46; doi:10.3390/pr5030046, 18 pages, http://www.mdpi.com/2227-9717/5/3/46/pdf
  14. X. Hong, B. Huang,*, Y.S. Ding, F. Guo, L. Chen, and L. Ren, Multi-model Multivariate Gaussian Process Modelling with Correlated Noises, Journal of Process Control, October 2017, 58, 11-22.
  15. R. Raveendran, B. Huang*, Two Layered Mixture Bayesian Probabilistic PCA for Dynamic Process Monitoring, Journal of Process Control, 2017, 57, 148-163
  16. S. Zhao, B. Huang*, Y. S. Shmaliy, Bayesian State Estimation on Finite Horizons: the Case of Linear State-Space Model, Automatica, Volume 85, 91-99, 2017
  17. R. Chi*, X. Liu, R. Zhang, Z. Hou, B. Huang, Constrained Data-driven Optimal Iterative Learning Control, Journal of Process Control, 2017, 55, 10-29
  18. F. Guo, H. Kodamana, B. Huang*, Y.S. Ding, Robust Identification of Nonlinear Errors-in-variables Systems with parameter Uncertainties Using Variational Bayesian Approach, IEEE Transactions on Industrial Informatics, June 2017, 13, 3047-3057
  19. CHI R., HUANG B., HOU Z., Optimal Iterative Learning Control of Batch Processes: From Model-based to Data-driven, ACTA Automatica Sinica (in Chinese), 2017, 43, 917-932
  20. X. Luan* , B. Huang, F. Liu, Higher order moment stability region for Markov jump systems based on cumulant generating function, Automatica, accepted April 2017
  21. F. Guo, O. Wu, Y. Ding, B. Huang*, A Data-based Augmented Model Identification Method for Linear Errors-in-Variables Systems Based on EM Algorithm, IEEE Transactions on Industrial Electronics, May 2017, 64, 8657-8665
  22. S. Zhao, B. Huang*, Iterative Residual Generator for Fault Detection with Linear Time-Invariant State-Space Models, IEEE Transaction on Automatic Control, October 2017, 62, 5422-5428
  23. R. Chi*, Z. Hou, S. Jin, B. Huang, An Improved Data-driven Point-to-Point ILC Using Additional On-line Control Inputs with Experimental Verification, IEEE Transactions on Systems, Man and Cybernetics: Systems, accepted April 2017, DOI: 10.1109/TSMC.2017.2693397
  24. F. Guo, O. Wu, H. Kodamana, Y. Ding, B. Huang*, An Augmented Model Approach for Identification of Nonlinear Errors-in-Variables Systems Using the EM Algorithm, IEEE Transactions on Systems, Man and Cybernetics: Systems, accepted April 2017,DOI: 10.1109/TSMC.2017.2692273
  25. M. Rashedi, J. Liu, B. Huang*, Distributed adaptive high-gain extended Kalman filtering for nonlinear systems, International Journal of Robust and Nonlinear Control, May 2017, 27,4873-4902
  26. A. Fatehi, B. Huang*,  State estimation and fusion in the presence of integrated measurement, IEEE Transactions on  Instrumentation & Measurement, 2017,66,2490-2499, DOI: 10.1109/TIM.2017.2701143
  27. A. Sadeghian, B. Huang*, Robust Probabilistic Principal Component Analysis Based Process Modeling: Dealing with Simultaneous Contamination of Both Input and Output Data, Journal of Process Control, accepted March 2017, doi: 10.1016/j.jprocont.2017.03.012
  28. F. Guo, H. Kodamana, B. Huang*, Y.S. Ding*, Robust Identification for Nonlinear Errors-in-variables Systems Using the EM Algorithm, Journal of Process Control, Volume 54, June 2017, Pages 129–137
  29. S. Sedghi, A. Sadeghian, B. Huang*, Mixture Semisupervised Probabilistic Principal Component Regression Model with Missing Inputs, Computers and Chemical Engineering, Volume 103, 4 August 2017, Pages 176–187
  30. Y. Ma, B. Huang*, Bayesian Learning for Dynamic Feature Extraction with Application in Soft Sensing, IEEE Transactions on Industrial Informatics, 2017, 64, 7171-7180 , DOI: 10.1109/TIE.2017.2688970
  31. R. Chi, Z. Hou, S. Jin, B. Huang*, Computationally-light Non-lifted Data-driven Norm-optimal Iterative Learning Control, Asian Journal of Control, accepted Feb 2017
  32. A. Fatehi, B. Huang, Kalman Filtering Approach to Multi-rate Information Fusion in the Presence of Irregular Sample Rate and Variable Measurement Delay, Journal of Process Control, Volume 53, May 2017, Pages 15–25
  33. S. Sedghi, B. Huang*, Real-time Assessment and diagnosis of Process Operating Performance, Engineering, 2017, 3(2): 214 -219
  34. E. Naghoosi, B. Huang*, Wavelet transform based methodology for detection and diagnosis of multiple oscillations in non-stationary variables, Industrial & Engineering Chemistry Research, Feb. 2017, 56 (8), pp 2083–2093
  35. W. Xiong, Y. Li, Y. Zhao, B. Huang*, Adaptive Soft Sensor Based on Time Difference Gaussian Process Regression with Local Time-delay Reconstruction, Chemical Engineering Research and Design, Volume 117, January 2017, Pages 670–680
  36. S. Zhao, B. Huang*, F. Liu, Detection and Diagnosis of Multiple Faults with Uncertain Modeling Parameters, IEEE Trans. on Control System Technology, 2017, 25, 1873-1881, DOI: 10.1109/TCST.2016.2624142
  37. Yuri A. W. Shardt*, B. Huang, Parameter-Based Conditions for Closed-Loop System Identifiability of ARX models with Routine Operating Data, Journal of the Franklin Institute, Volume 354, January 2017, Pages 722-751
  38. X. Yuan, Z. Ge, B. Huang*, Z. Song, Semi-supervised JITL framework for nonlinear industrial soft sensing based on locally semi-supervised weighted PCR, IEEE Transactions on Industrial Informatics, Volume: 13, Issue: 2, April 2017
  39. R. Chi*, N. Lin, R. Zhang, B. Huang, Y. Feng, Stochastic High-order Internal Model based Adaptive TILC with Random Uncertainties in Initial States and Desired Reference Point, International Journal of Adaptive Control and Signal Processing,2017, 31, 726-741
  40. Y. Zhao, A. Fatehi, B. Huang*, A data-driven hybrid ARX and Markov-Chain modeling approach to process identification with time varying time delays, IEEE Trans on Industrial Electronics, Volume: 64, Issue: 5, May 2017, 4226 - 4236
  41. X. Yuan, Z. Ge, B. Huang*, Z. Song, A probabilistic just-in-time learning framework for soft sensor development with missing data, IEEE Trans on Control Systems Technology, DOI: 10.1109/TCST.2016.2579609,Volume: 25, Issue: 3, May 2017
  42. Y. Yuan, Z. Li*, B. Huang, Robust Optimization Approximation for Joint Chance Constrained Optimization Problem, Journal of Global Optimization, April 2017, Volume 67, Issue 4, pp 805–827
  43. S. Zhao, B. Huang*, F. Liu, Linear Optimal Unbiased Filter for Time-Variant Systems without Apriori Information on Initial Conditions, IEEE Trans. On Automatic Control, Volume: 62, Issue: 2, Feb. 2017,882 - 887
  44. E. Naghoosi, B. Huang, Interaction analysis of multivariate control systems under Bayesian framework, IEEE Trans on Control Systems Technology, Volume: 25, 2017, 1644-1655.
  45. L. Cao, Y. Tao, Y. Wang*, J. Li, B. Huang, Reliable H∞ Control for Nonlinear Discrete-Time Systems with Multiple Intermittent Faults in Sensors or Actuators, International Journal of Systems Science, Volume: 48, 2017, 302-315.