Dr. Michael Nikolaou
Professor of Chemical and Biomolecular Engineering
Director MChE Engineering Program

Dept. of Chemical and Biomolecular Engineering
University of Houston
4800 Calhoun Ave.
Houston, TX 77204-4004
Office Location: S228
Telephone: (713) 743-4309
Fax: (713) 743-4323
E-mail: nikolaou "at-sign" uh "dot" edu

› EDUCATION    › RESEARCH    › TEACHING INTERESTS     › PUBLICATIONS                                               

› Information on the only Nobel Prize awarded for work on chemical process control

EDUCATION

— Diploma National Technical University, Athens, Greece (1984)
— Ph.D. University of California, Los Angeles (1989)

RESEARCH INTERESTS

Hard to define yet easy to recognize, intelligence as a feature in the operation of engineered systems is highly desirable and increasingly possible. Whether one deals with a chemical plant, an offshore oil-production platform, a food-processing facility, a microchip making factory, or a medicated human patient, intelligent operation of a system offers distinct advantages, ranging from high return on investment to improved quality, reliability, and safety. Computer software and hardware (from a simple chip to a full computer) and their interaction with humans are at the heart of intelligent operations. The ubiquitous concept of feedback is the basic underlying principle. While the computer is the “brains”, all elements of a feedback loop (including sensors, actuators, and transmission / communication lines) are important and have experienced unprecedented advancement in recent years. In this context, our research aims at the development of

• new fundamental methods for the solution of broad classes of intelligent operations problems, and
• solutions for specific problems of real-world importance.

There are several tools of quantitative analysis employed by our group, including system modeling and identification, optimization, statistics, and feedback control. In addition, domain expertise in the various fields where we conduct our research is of paramount importance. As a consequence, our work has a strong interdisciplinary flavor and often builds on collaboration with investigators from other fields. Solutions proposed by our work are tested using computer simulations, laboratory experiments, or industrial-site tests. Examples of on-going research areas include the following:

• Oil and gas production systems: What hardware and software technologies can be used in the field to safely maximize return-on-investment?
• Semiconductor manufacturing tools and processes: How can equipment be designed and operated that ensures consistent production of high-quality microchips?
• Effective development and use of antibiotics: How can new antibiotics and clinical practices be designed that maximize the killing effect of antibiotics on pathogenic bacteria while minimizing toxicity for human patients?

Our collaboration with field practitioners is an essential element in our quest for fundamental solutions to problems or relevance to the real world. Many of our students conduct part of their research at industrial collaborator sites – both in the Houston area and elsewhere – a practice that offers many clear benefits to all parties involved. Over 15 Ph.D. students graduating from our group have landed successful careers in diverse industrial areas, such as oil and gas, refining, chemicals, semiconductor, engineering design, and food processing, as well as in academia.

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Teaching Interests

Courses Taught

Undergraduate

• Numerical Methods for Chemical Engineers
• Plant Economics
• Plant Design
• Thermodynamics
• Statistical Methods in Chemical Engineering (senior elective)
• Statistical Quality Control Methods (senior elective)
• Seminar (written and oral presentations for chemical engineers)
• Process Control

Graduate

• Mathematical Methods in Chemical Engineering
• Advanced Process Control

Teaching philosophy

It is rather well accepted, that the teaching of chemical engineering is at a stage of evolution, due to two factors:

• Recent advances and broadening of chemical engineering science and technology.
• Developments in teaching technology, in part owed to new capabilities of electronic media.

Academia needs to constantly assess, and possibly improve, what and how to teach. Improvements may be realized in two ways: Step changes, e.g. new courses, and gradual modification of existing courses.

What and how to teach

The scope of academic teaching is clear: Teach the fundamentals, so that students can later learn on their own as well. From that point of view, current chemical engineering curricula have well known strengths, such as breadth and flexibility. However, industrial relevance is of paramount importance for consolidating the fundamentals. My activities related to teaching include the following:

• Communication with the Dept.’s industrial advisory council. Responding to their suggestion, I developed the statistical process control (SPC) part (50%) of a new undergraduate course. I also developed an undergraduate course on Statistical Methods in Chemical Engineering.
• Interaction with students and colleagues. Within the Chemical Engineering Dept., I chair curriculum committees that biannually critique the content of each course (rather than the instructor), for consistency, continuity, and continual improvement.
• Incorporation of widespread recent chemical engineering discoveries in undergraduate courses, and consolidation of research results into graduate courses (e.g., graduate course on Advanced Control, new computing methodologies and software tools).
• Incorporation of practical experience (e.g., consulting) in course material.
• Use of modern instructional media (e.g., interactive presentation of PC graphics during lecturing).
• Participation in engineering education seminars and conferences (e.g. ASEE Annual Meeting).
• Study of relevant literature on the teaching of engineering.

Undergraduate research

Our group has advised over a dozen undergraduate students, a number of whom have continued with graduate studies.

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(Postscript file viewer - free download)

SELECTED PUBLICATIONS

Patents

Economides, Michael J.; Deeg, Wolfgang F. J.; Valko, Peter; Nikolaou, Michael; and Sankaran, Sathish, Method for stress and stability related measurements in boreholes, U.S. Patent 6,834,233, 2004.

Refereed Journal Publications

1. Nikolaou, M. and V. Manousiouthakis, "A Hybrid Approach to Nonlinear System Stability and Performance", AIChE Journal, 35, 4, 559-572 (1989).
2. Manousiouthakis, V. and M. Nikolaou, "Analysis of Decentralized Control Structures for Nonlinear Systems", AIChE Journal, 35, 4, 549-558 (1989).
3. Nikolaou, M. and V. Manousiouthakis, "Sensitivity Analysis of Optimal Control Policies for Batch Processes", Chemical Engineering Communications 97, 27-45 (1990).
4. Fan, J. Y., M. Nikolaou, and R. E. White, "An Approach to Fault Diagnosis of Chemical Processes via Neural Networks", AIChE J. 39, 1, 82-88 (1993).
5. You, Y., and M. Nikolaou, "Dynamic Process Modeling with Recurrent Neural Networks", AIChE J., 39, 10, 1654-1667 (1993).
6. Nikolaou, M. and V. Hanagandi, "Input-Output Exact Linearization of Nonlinear Dynamical Systems Modeled by Recurrent Neural Networks", AIChE J., 39, 11, 1890-1894 (1993).
7. Genceli, H., and M. Nikolaou, "Robust Stability Analysis of Constrained l1-Norm Model Predictive Control", AIChE J., 39, 12, 1954-1965 (1993).
8. Holtzapple, M. T., E. P. Ripley, and M. Nikolaou, "Saccharification, Fermentation, and Protein Recovery from AFEX-Treated Coastal Bermudagrass", Biotechnology and Bioengineering, 44, 1112–1131 (1994).
9. Nikolaou, M., and V. Hanagandi, "Recurrent Neural Networks in Decoupling Control of Multivariable Nonlinear Systems", Chem. Eng. Communications, 136, 201-216 (1995).
10. Vuthandam, P., H. Genceli, and M. Nikolaou, "Performance Bounds of Robust Model-Predictive Control", AIChE J., 41, 9, 2083-2097 (1995).
11. Genceli, H. and M. Nikolaou, "Design of Robust Constrained Nonlinear Model Predictive Controllers with Volterra Series", AIChE J., 41, 9, 2098-2107 (1995).
12. Hanagandi, V., H. Ploehn, and M. Nikolaou, "Solution of the Self-Consistent Field Model for Polymer Adsorption by Genetic Algorithms", Chem. Eng. Sci. , 51, 7, 1071-1078 (1996).
13. Sarimveis, H., H. Genceli, and M. Nikolaou, "Design of Robust Non-Square Constrained Model Predictive Control", AIChE J., 42, 9, 2582-2593 (1996).
14. Genceli, H., and M. Nikolaou, "New Approach to Constrained Predictive Control with Simultaneous Model Identification", AIChE J., 42, 10, 2857-2869 (1996).
15. Choi, J., M. Nikolaou, and V. Manousiouthakis, "Nonlinear System Gains and Incremental Gains over Ball", IEEE Trans. AC, accepted (1996).
16. Hanagandi, V., and Nikolaou, M. "A Hybrid Approach to Global Optimization Using a Clustering Algorithm in a Genetic Search Framework," Computers Chem. Engng., 22, 12, 1913-1925 (1998).
17. Nikolaou, M., and V. Hanagandi, "Nonlinearity Quantification and its Application to Nonlinear System Identification", Chem. Eng. Comm., 166, 1-33 (1998).
18. Shouche M., H. Genceli, P. Vuthandam, and M. Nikolaou, "Simultaneous Constrained Model Predictive Control and Identification of DARX Processes", Automatica, 34, 12, 1521-1530 (1998).
19. Moridis, G. J., M. Nikolaou, and Y. You, "The Use of Wavelet Transforms in the Solution of Two-Phase Flow Problems", SPE J., (1996).
20. Vuthandam, P., and M. Nikolaou, "Constrained Model Predictive Control and Identification: A Weak Persistent Excitation Approach", AIChE J., 43, 9, 2279-2288 (1997).
21. Nikolaou, M., and P. Vuthandam, "FIR Model Identification: Achieving Parsimony through Kernel Compression with Wavelets", AIChE J., 44, No. 1, 141-150 (1998).
22. Schwarm, A., and M. Nikolaou, "Chance Constrained Model Predictive Control", AIChE Journal, 45, 8, 1605-1844 (1998).
23. Eker, S. A., and M. Nikolaou, "Adaptive Control through On-line Optimization: The MPCI Paradigm and Variants", Appl. Math. And Comp. Sci., 9, 1, 101-128 (1999).
24. Nikolaou, M., "Identification and Adaptive Control", Comp. Chem. Eng., special issue on NSF/NIST Vision 2020 Workshop, 23/2, pp. 215 - 225, (1998).
25. Nikolaou, M., and M. Cherukuri, "Connection between Model Predictive Control and Anti-Windup Control Schemes", Automatica, re-submitted (2001).
26. Haarsma, G. J., and M. Nikolaou, "Multivariate Controller Performance Monitoring: Lessons from an Application to a Snack Food Process", submitted to Journal of Process Control (2000).
27. Eker, S. A., and M. Nikolaou, "Simultaneous Model Predictive Control and Identification: Closed-Loop Properties", Automatica (submitted) (2001).
28. Eker, S. A., and M. Nikolaou, "Ensuring Co-primeness in Least-Squares Identification of ARX Models: The SICLS algorithm", Automatica (submitted) (2001).
29. Saputelli, L., B. Cherian, K. Grigoriadis, M. Nikolaou, C. Oudinot, G. Reddy, M. J. Economides, and C. Ehlig-Economides, "Integration of Computer-Aided High-Intensity Design with Reservoir Exploitation of Remote and Offshore Locations", SPE J., accepted (2001).
30. Shouche, M., H. Genceli, and M. Nikolaou, "Effect of on-line optimization techniques on model predictive control and identification (MPCI)", Comp. and Chem. Eng., 26, 9: 1241-1252 (2002).
31. Eker SA, Nikolaou M, "Linear Control of Nonlinear Systems - The Interplay between Nonlinearity and Feedback", AIChE J., 48, 9: 1957-1980 (2002).
32. Zhang HY, Nikolaou M, Peng Y, "Development of a Data Driven Dynamic Model for a Plasma Etching Reactor", J. Vac. Sci. Tech. B, 20, 3: 891-901 (2002).
33. Misra P, Nikolaou M, "Input Design for Model Order Determination in Subspace Identification", AIChE J., 49, 8: 2124-2132 (2003).
34. Nikolaou M, Misra P, "Linear Control of Nonlinear Processes: Recent Developments and Future Directions", Comp. and Chem. Eng., 27, 8-9: 1043-1059 (2003).
35. Nikolaou, M. (2006). Control of snack food manufacturing systems. IEEE Control Systems Magazine, 26(4), 40-53.
36. Nikolaou, M., Misra, P., Tam, V. H. & Bailey, A. D. (2005). Complexity in semiconductor manufacturing, activity of antimicrobial agents, and drilling of hydrocarbon wells: Common themes and case studies. Computers & Chemical Engineering, 29(11-12), 2266-2289.
37. Nikolaou, M. & Tam, V. H. (2006). A new modeling approach to the effect of antimicrobial agents on heterogeneous microbial populations.Journal Of Mathematical Biology, 52(2), 154-182.
38. Saputelli, L., Nikolaou, M. & Economides, M. J. (2005). Self-learning reservoir management. SPE Reservoir Evaluation & Engineering, 8(6), 534-547.
39. Saputelli, L., Nikolaou, M. & Economides, M. J. (2006). Real-time reservoir management: A multiscale adaptive optimization and control approach. Computational Geosciences, 10(1), 61-96.
40. Tam, V. H. & Nikolaou, M. (2005). Mathematical modelling of resistance emergence. Journal Of Antimicrobial Chemotherapy, 56(5), 983-983.
41. Tam, V. H., Schilling, A. N. & Nikolaou, M. (2005). Modelling time-kill studies to discern the pharmacodynamics of meropenem. Journal Of Antimicrobial Chemotherapy, 55(5), 699-706.
42. M. L. Darby, and M. Nikolaou (2007).  A parametric programming approach to moving-horizon state estimation.  Automatica, 43(5), 885-891.
43. Nikolaou, M., Schilling, A. N., Vo, G., Chang, K.-t. & Tam, V. H. (2007). Modeling of Microbial Population Responses to Time-Periodic Concentrations of Antimicrobial Agents. Annals of Biomedical Engineering, 35(8), 1458-1470.
44. Darby, M. L. and M. Nikolaou (2007).  Multi-variable system identification for integral controllability.  Automatica, submitted.
45. Tam, V. H., A. N. Schilling, K. Poole, and M. Nikolaou (2007). Mathematical modelling response of Pseudomonas aeruginosa to meropenem.  J. Antimicrob. Chemother., Advance Access published on October 3, 2007; doi: doi:10.1093/jac/dkm370

Book Chapters

Nikolaou, M., and Y. You, "Use of Wavelets for Numerical Solution of Differential Equations", Wavelet Applications in Chemical Engineering, B. Joseph and R. Motard Eds., 209-274, Kluwer (1994).

Hanagandi, V., and M. Nikolaou, "Applications of Genetic Algorithms in Chemical Engineering", Practical Handbook of Genetic Algorithms, Lance Chambers Ed., Volume 2, 221-252, CRC Press (1995).

Nikolaou, M., "Model Predictive Controllers: A Critical Synthesis of Theory and Industrial Needs", Advances in Chemical Engineering Series, Academic Press (2001). (Zip-compressed version)

Nikolaou, M., “Combating microbial resistance to antimicrobial agents through dosing regimen optimization”, Optimization in Medicine and Biology, G. Lim (Editor), Taylor & Francis, in print (2007).

Major Reports

Nikolaou, M., Jesse L. Buffington, Angel Herrera, Jr., and Hwang Inkeuk, Traffic Air Pollution Effects of Elevated, Depressed, and at-Grade Level Freeways in Texas, FHWA/TX-97/1327-4, Texas Transportation Institute, The Texas A&M University System, College Station, Texas 77843-3135 (1997).

Conference Proceedings Publications

Manousiouthakis, V. and M. Nikolaou, "On the Nonlinear Block Relative Gain", Proceedings of the American Control Conference, Seattle, WA, 2120-2125 (1987).

Nikolaou, M. and V. Manousiouthakis, "A Hybrid Approach to Nonlinear System Theory", Proceedings of the 26th IEEE Conference on Decision and Control, Century City, CA, 2127-2132 (1987).

Nikolaou, M. and V. Manousiouthakis, "Robust Control of Batch Processes", Proceedings of the American Control Conference, Atlanta, GA, 665-670 (1988).

Nikolaou, M. and V. Manousiouthakis, "On the Characterization and Evaluation of Stability of Nonlinear Systems", Proceedings of the American Control Conference, Atlanta, GA, 1559-1564 (1988).

Nikolaou, M. and V. Manousiouthakis, "Stability Aspects of Exact Linearization Methods: A Hybrid Approach", Proceedings of the American Control Conference, San Diego, CA, 2736-2740 (1990).

Nikolaou, M. and H. Genceli, "Establishing Performance Targets for Model Predictive Control Systems through off-line Optimization", Proceedings of the American Control Conference, Boston, MA, 1822-1823 (1991).

Nikolaou, M., and H. Sarimveis, "Process Modeling with Recurrent Neural Networks", ANNIE 91 Proceedings (1991).

Nikolaou, M., and V. Hanagandi, "Input-Output Exact Linearization of Nonlinear Dynamical Systems Modeled by Recurrent Neural Networks", ANNIE 91 Proceedings, St. Louis, MO (1991).

Nikolaou, M., "When is Nonlinear Dynamic Modeling Necessary?", ACC Proceedings, 910-914, San Francisco, CA (1993).

Nikolaou, M., "Neural Network Modeling of Nonlinear Dynamical Systems", ACC Proceedings, 1460-1464, San Francisco, CA (1993).

Moridis, G. J., and M. Nikolaou, "The Laplace Transform Wavelet (LTW) Method for the Solution of the Equations of Flow and Transport Through Porous Media", EOS Trans. AGU, 74, 43, 307 (1993).

Vuthandam, P., H. Genceli, and M. Nikolaou, "Analysis and Synthesis Methods for Robust Model Predictive Control", ADCHEM’94 Proceedings, Kyoto, JAPAN (1994).

Nikolaou, M., "The 2-norm for Nonlinear Processes: Application to Modeling and Control Problems", PSE’94 Proceedings, Kyongju, KOREA (1994).

Nikolaou, M., "Teaching Numerical Methods Using Interactive Computer Spreadsheets in Class", Proceedings of ASEE Annual Conference, Session 3162, 2731-2736, Edmonton, Canada (1994).

Genceli, H., P. Vuthandam, and M. Nikolaou, "Analysis and Synthesis Methods for Robust Model Predictive Control", NATO ASI on Model Based Process Control, 235-262, Antalya, Turkey (1994).

Moridis, G. J., M. Nikolaou, and Y. You "The Use of Wavelet Transforms in the Solution of Two-Phase Flow Problems", Proceedings of SPE 13th Symposium on Reservoir Simulation, 521-530, San Antonio, TX (1995).

Hanagandi, S. Brown, R. Sherman, R. Jones, and M. Nikolaou, "Control Strategies for the TSTA Distillation Column I", ACC Proceedings, 2653-2656 (1995).

Nikolaou, M., "Computer-Aided Process Engineering in the Snack Food Industry", CPC V preprints, Tahoe City, CA (1996).

Genceli, H., and M. Nikolaou, "A new approach to model predictive control and identification", 1996 IFAC World Congress Proceedings, San Francisco (July 1996).

Sarimveis, H., H. Genceli, and M. Nikolaou, "Design of Robust Non-Square Constrained Model Predictive Control", to be included in European Symposium on Computer-Aided Process Engineering Proceedings, Rhodes, Greece (May, 1996).

Genceli, H., and M. Nikolaou, "A New Approach to Constrained Predictive Control with Simultaneous Model Identification", to be included in European Symposium on Computer-Aided Process Engineering Proceedings, Rhodes, Greece (May, 1996).

Nikolaou, M., "Directions in Computer-Aided Process Engineering", AIChE World Congress Proceedings, San Diego, CA (1996).

Nikolaou, M., and B. Joseph, "Intelligent Control", ISPE 95 Proceedings, 68-69 (1996).

Nikolaou, M., and D. Mantha, "Efficient nonlinear modeling using wavelets and related compression techniques", NSF Workshop on Nonlinear Model Predictive Control, Ascona, CH (1998). (Group photo)

Sankaran, S., M. Nikolaou, and M. J. Economides, "Fracture Geometry and Vertical Migration in Multilayered Formations from Inclined Wells", paper SPE 63177, SPE Annual Meeting, Dallas (2000).

Zhang, H., and M. Nikolaou, "Control of Spatial Uniformity in Microelectronics Manufacturing: An Integrated Approach", APC/AEC XII Sematech Workshop, Lake Tahoe (2000).

Nikolaou, M., and A. D. Bailey, III, “Application of reduced-rank multivariate methods to the monitoring of spatial uniformity of wafer etching”, MASM 2002.

M. Nikolaou, A.S. Cullick, L. Saputelli, G. Mijares, and S. Sankaran, L. Reis, A Consistent Approach Toward Reservoir Simulation at Different Time Scales,  SPE  99451-MS (2006)

M. Nikolaou, A.S. Cullick and L. Saputelli, Production Optimization—A Moving-Horizon Approach,  SPE  99358-MS (2006)

Ankur Awasthi, Sathish Sankaran, Michael Nikolaou, Luigi Saputelli, and Gerardo Mijares, Closing the Gap Between Reservoir Modeling and Production Optimization,  SPE  107463-MS (2007)

Luigi Saputelli, Bilu Cherian, Karolos Gregoriadis, Michael Nikolaou, Cedric Oudinot, Gopal Reddy, Michael J. Economides, Christine Ehlig-Economides, Integration of Computer-Aided High-Intensity Design with Reservoir Exploitation of Remote and Offshore Locations,  SPE  64621-MS (2000)

L. Saputelli, M. Nikolaou, M.J. Economides, Self-Learning Reservoir Management,  SPE  84064-MS (2003)

L. Saputelli, H. Malki, J. Canelon, M. Nikolaou,  A Critical Overview of Artificial Neural Network Applications in the Context of Continuous Oil Field Optimization,  SPE  77703-MS (2002) 

Sathish Sankaran, Wolfgang Deeg, Michael Nikolaou, Michael J. Economides,  Measurements and Inverse Modeling for Far-Field State of Stress Esimation, SPE  71647-MS (2001)

L. Saputelli, M. Economides, M. Nikolaou, V. Kelessidis,  Real-time Decision-making for Value Creation while Drilling, SPE  85314-MS (2003)

A. Awasthi, S. Sankaran, M. Nikolaou, L. Saputelli and G. Mijares (2007). Closing the Gap Between Reservoir Modeling and Production Optimization. SPE 107463-MS

A. Awasthi, S. Sankaran, M. Nikolaou, L. Saputelli, & G. Mijares (2008). Short-Term Production Optimization by Automated Adaptive Modeling and Control.  SPE 112239-MS

A. Awasthi, S. Sankaran, M. Nikolaou, L. Saputelli, and G. Mijares (2008). Meeting the Challenges of Real-Time Production Optimization: A Parametric Model-Based Approach.  SPE 111853-MS

L. A. Carlsen, G. Nygaard, J. E. Gravdal, M. Nikolaou, J. Schubert (2008). Performing the Dynamic Shut-In Procedure Because of a Kick Incident When Using Automatic Coordinated Control of Pump Rates and Choke-Valve Opening. SPE 113693-MS

 

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