Lester  Lik Teck Chan(田立德)

  • 學歷：Ph.D. Chemical Engineering  (Chung-Yuan Christian University), Taiwan
                M.S. Chemical Engineering, NTUST, Taiwan
                B.S. Chemical Engineering, UMIST, Manchester, U.K.

  • 論文題目：Gaussian Process Model Based Process Identification, Control and Performance Assessment: Data Selection for Model Uncertainty Improvement

  • 博士班103級畢

  • 現職：中原大學化工系助理教授 (2019-8~)
                 逢甲大學化工系助理教授 (2018-8~2019-7)

  • 研究方向：Transfer Learning; Integration Process Design and Process Control

發表論文：

  • L. L. T. Chan and J. Chen, Gaussian Process Model Based Multi-Source Labeled Data Transfer Learning for Reducing Cost of Modeling Target Chemical Processes with Unlabeled Data, Control Eng. Pract,,  2021.  (Accepted)
  • X. Wu, J. Chen, L. Xie, L. L. T. Chan  and C.-I. Chen, Development of Convolutional  Neural Network Based Gaussian Process Regression to Construct a Novel Probabilistic Virtual Metrology in Multi-Stage Semiconductor Processes, Control Eng. Pract, 96, 104262, 2020
  • Z. Zhang, L. L. T. Chan, J. Chen and Z. Shao, Correntropy Based Data Reconciliation and Gross error Detection for Bilinear Systems, Chem. Eng. Sci., 212, 115327, 2020.

  • L. L. T. Chan and J. Chen, Improving the Energy Cost of an Absorber-Stripper CO2 Capture Process through Economic Model Predictive Control, International Journal of Greenhouse Gas Control., 76, 158-166, 2018.

  • L. L. T. Chan and J. Chen, Economic Model Predictive Control of Distillation Startup Based on Probabilistic Approach, Chem. Eng. Sci., 186, 26-35, 2018.

  • X. Feng, D. Li, J. Chen, M. Niuc, X. Liu, L. L. T. Chan and W. Li, Kinetic Parameter Estimation and Simulation of Trickle-bed Reactor for Hydrodesulfurization of Whole Fraction Low-Temperature Coal Tar, Fuel, 230 113-125, 2018.

  • L. L. T. Chan, X. Wu, J. Chen, L. Xie and C.-I. Chen, Just-In-Time Modeling with Variable Shrinkage Based on Gaussian Processes for Semiconductor Manufacturing, IEEE Transactions on Semiconductor Manufacturing, 31(3) 1-8, 2018.

  • L. L. T. Chan, Q.-Y. Wu, and J. Chen, Dynamic Soft Sensors with Active Forward-Update Learning for Selection of Useful Data from Historical Big Database,  Chemometer Intell. Lab., 175, 87-103, 2018.

  • L. L. T. Chan and J. Chen, Probabilistic Uncertainty Based Simultaneous Process Design and Control with Iterative Expected Improvement Model,  Computers & Chemical Engineering, 106, 609-620, 2017.

  • L. L. T. Chan and J. Chen, Melt Index Prediction Using Mixture of Gaussian Process Regression with Embedded Clustering and Variable Selections,  Journal of Applied Polymer Science, 134, 45237, 2017.

  • L. L. T. Chan, C.-P. Chou, and J. Chen, Hybrid Model Based Expected Improvement Control for Cyclical Operations of Microfiltration Membrane Processes,  Chem. Eng. Sci., 166, 77-90, 2017.

  • L. L. T. Chan, T. Chen and J. Chen, PID Based Nonlinear Processes Control Model Uncertainty Improvement by Using Gaussian Process Model , J. Process Contr., 42, 77-89, 2016.

  • L. L. T. Chan, Y. Liu and J. Chen,  Nonlinear System Identification with Selective Recursive Gaussian Process Models, Ind. Eng. Chem. Res. 52 (51) 18276-18286, 2013.

  • J. Chen, L. L. T. Chan and N. Cheng, Gaussian Process Regression Based Optimal Design of Combustion Systems Using Flame Images, Applied Energy, 111, 153-160, 2013.

  • J. Chen, M.-H. Chen and L. L. T. Chan, Iterative Learning Parameter Estimation and Design of SMB Processes, Chemical Engineering Journal, 161, 223-233, 2010.

  • J. Chen, K.-T. Hsieh and L. L. T. Chan, Wave Propagation Velocities in Integrated PLS Based Control of a Simulated Moving Bed Process, Chem. Eng. Sci., 65, 2990-3000, 2010.

  • J. Chen, K.-T. Hsieh and L. L. T. Chan, PLS Data-Driven Based Approach to Design of a Simulated Moving Bed Process, Sep. Purif. Technol., 65, 173-183, 2009
  • Y.-C. Zhang, L. L. T. Chan and J. Chen, Application of Convolutional Neural Network Based Variational Auto-encoder Model to the Image Monitoring of Combustion Processes, 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), Sept. 23-26, 2020, Chiang Mai, Thailand. (Accepted)
  • L. L. T. Chan,  and J. Chen, Reducing Cost of Process Modeling through Multi-source Data Transfer Learning, 12th Asian Control Conference (ASCC), June. 9-12, 2019, Fukuoka, Japan. (Accepted).
  • L. L. T. Chan, Y.-S. Lee and J. Chen, Economic Model Predictive Control of CO2 Capture Process Retrofitted with Membrane Units, 6th International Symposium on Process Intensification, Nov. 7-8, 2018, Taipei, Taiwan.
  • Y.-S. Lee, O.-S. Kit, D. Tanny, L. L. T. Chan and J. Chen, Reducing Energy Cost of Absorber-Stripper CO2 Capture Process through Economic Neural Network Model Predictive Control, 6th International Symposium on Process Intensification, Nov. 7-8, 2018, Taipei, Taiwan.
  • L. L. T. Chan,  and J. Chen, Economic Model Predictive Control of an Absorber-Stripper CO2 Capture Process for Improving Energy Cost, 10th International Symposium on Advanced Control of Chemical Processes (ADCHEM), July 25-27, 2018, Shenyang, China.
  • S. W. Ku, J. Chen and L. L. T. Chan, Identification of LTV Systems with Cascade Control Loops Using Basis Function Approach, 6th International Symposium on Advanced Control of Industrial Processes (ADCONIP 2017), 28-31 May, 2017, Taipei.
  • Q.-Y. Wu, L. L. T. Chan and J. Chen, Active Learning Dynamic Soft Sensor with Forward-Update Scheme, 6th International Symposium on Advanced Control of Industrial Processes (ADCONIP 2017), 28-31 May, 2017, Taipei.
  • X. Wu, L. L. T. Chan, J. Chen and X. Lei, Application of Gaussian Processes with Variable Shrinkage Method and Just-In-Time Modeling in the Semiconductor Industry, 6th International Symposium on Advanced Control of Industrial Processes (ADCONIP 2017), 28-31 May, 2017, Taipei.
  • J. Chen, L. L. T. Chan and Q.-Y. Wu, Utilizing Big Data for Development of Soft Sensor, AIChE's 2017 Spring Meeting and 13th Global Congress on Process Safety,  26-30 Mar. 2017, San Antonio, US.
  • L. L. T. Chan,  C.-P. Chou and J. Chen,  Hybrid Model Based Control for Membrane Filtration Process, 11th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems (DYCOPS-CAB 2016),   Trondheim, Norway, June 6-8, 2016.
  • L. L. T. Chan and J. Chen, Gaussian Process Model Based Performance Assessment of Control Loop, 17th IFAC Symposium on System Identification (SYSID 2015),  Oct 19-21, 2015 , Beijing.
  • L. L. T. Chan, Z. Ge and J. Chen, A Distributed Modeling Framework for Monitoring Big Data in Plant-Wide Processes, AIChE's 2015 Spring Meeting and 11th Global Congress on Process Safety,  26-30 Apr. 2015, Austin, US.
  • L. T. L. Chan, T. Chen, J. Chen, Applying Gaussian Process Models to On-line Enhancement of PID Control Design for Nonlinear Processes, 5th  International Symposium on Advanced Control of Industrial Processes (ADCONIP 2014), 28-30 May, 2014, Hiroshima, Japan.
  • T.-Y. Hsu, L. C. L. Teck, J. Chen, M.-T. Liang, R.-C. Liang, Fault Monitoring of SMB Processes Using Visualized On-Line Concentration Patterns, 2008 Taiwan/Korea/Japan ChE Conference, 20-22 Nov. 2008, Taipei, Taiwan.
  • T.-Y. Hsu, L. L. T. Chan, J. Chen, M.-T. Liang, R.-C. Liang, Modeling Study of On-Line Estimation of SMB Parameters in Mixture of Quercetin and Rutin, International Symposium on Preparative & Industrial Chromatography and Allied Techniques, SPICA 2008, Sep. 28--Oct. 1, 2008, Zurich, Switzerland.
  • K.-T. Hsieh, L. L. T. Chan, and J. Chen, PLS-based Iterative Control of a Simulated Moving Bed, PSE Asia 2007, Aug 2007, Xi'an, China.