Chemical & Biomolecular Engineering

Top 20 Doctoral Program—National Research Council

Location

Dept. of Chemical & Biomolecular Engineering
University of Houston
S222 Engineering Bldg 1,
Houston, TX 77204-4004
phone: 713-743-4300

Faculty

Dr. Michael Nikolaou

Professor of Chemical and Biomolecular Engineering

Office Location: S228, Engineering Building 1

Tel: (713) 743-4309 | Fax: (713) 743-4323

Email: nikolaou [at] uh [dot] edu

Education

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

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

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
  • Introduction to Computing

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.

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.

Selected Publications

  1. Bhagunde, P.; Singh, R.; Ledesma, K. R.; Chang, K. T.; Nikolaou, M.; Tam, V. H.,,

    Modelling biphasic killing of fluoroquinolones: guiding optimal dosing regimen design. Journal of Antimicrobial Chemotherapy 2011, 66 (5), 1079-1086.

    , 2011
  2. Breyholtz, O.; Nygaard, G.; Nikolaou, M.,,

    Managed-Pressure Drilling: Using Model Predictive Control To Improve Pressure Control During Dual-Gradient Drilling. Spe Drilling & Completion 2011, 26 (2), 182-197.

    , 2011
  3. Darby, M. L.; Nikolaou, M.; Jones, J.; Nicholson, D.,,

    RTO: An overview and assessment of current practice. Journal of Process Control 2011, 21 (6), 874-884.

    , 2011
  4. Economides, M. J.; Nikolaou, M.,,

    Technologies for Oil and Gas Production: Present and Future. Aiche Journal 2011, 57 (8), 1974-1982.

    , 2011
  5. Guo, B. N.; Abdelraouf, K.; Ledesma, K. R.; Chang, K. T.; Nikolaou, M.; Tam, V. H.,,

    Quantitative Impact of Neutrophils on Bacterial Clearance in a Murine Pneumonia Model. Antimicrobial Agents and Chemotherapy 2011, 55 (10), 4601-4605.

    , 2011
  6. Tam, V. H.; Nikolaou, M.,,

    A Novel Approach to Pharmacodynamic Assessment of Antimicrobial Agents: New Insights to Dosing Regimen Design. Plos Computational Biology 2011, 7 (1).

    , 2011

Journal Papers / Refereed Journal Publications

  1. Bhagunde, P., R. Singh, K. R. Ledesma, K. T. Chang, M. Nikolaou and V. H. Tam,

    “Modelling biphasic killing of fluoroquinolones: guiding optimal dosing regimen design,” Journal of Antimicrobial Chemotherapy, 66(5): 1079-1086

    , 2011
  2. Breyholtz, O., G. Nygaard and M. Nikolaou,

    “Managed-Pressure Drilling: Using Model Predictive Control To Improve Pressure Control During Dual-Gradient Drilling,” SPE Drilling & Completion, 26(2): 182-197

    , 2011
  3. Darby, M. L., M. Nikolaou, J. Jones and D. Nicholson,

    “RTO: An overview and assessment of current practice,” Journal of Process Control, 21(6): 874-884

    , 2011
  4. Diomede, P., M. Nikolaou and D. J. Economou,

    “Voltage waveform to achieve a desired ion energy distribution on a substrate in contact with plasma,” Plasma Sources Science & Technology, 20(4)

    , 2011
  5. Economides, M. J. and M. Nikolaou,

    “Technologies for Oil and Gas Production: Present and Future,” AIChE Journal, 57(8): 1974-1982. (Exceprted in Chemical Engineering Progress, 8:12)

    , 2011
  6. Guo, B. N., K. Abdelraouf, K. R. Ledesma, K. T. Chang, M. Nikolaou and V. H. Tam,

    “Quantitative Impact of Neutrophils on Bacterial Clearance in a Murine Pneumonia Model,” Antimicrobial Agents and Chemotherapy, 55(10): 4601-4605

    , 2011
  7. Guo, B., Abdelraouf, K., Ledesma, K., Nikolaou, M., Tam, V.,

    “Predicting bacterial fitness cost associated with drug resistance,” Journal of Antimicrobial Chemotherapy, accepted

    , 2011
  8. Tam, V. H. and M. Nikolaou,

    “A Novel Approach to Pharmacodynamic Assessment of Antimicrobial Agents: New Insights to Dosing Regimen Design,” PLoS Computational Biology, 7(1). (Featured Article;  Reviewed at Priority Paper Evaluation by J. Mouton, Future Microbiol., 6(6), 613–616)

    , 2011
  9. Bhagunde, P., K. T. Chang, R. Singh, V. Singh, K. W. Garey, M. Nikolaou and V. H. Tam,

    “Mathematical Modeling To Characterize the Inoculum Effect,” Antimicrobial Agents and Chemotherapy, 54(11): 4739-4743

    , 2010
  10. Gravdal, J. E., M. Nikolaou, O. Breyholtz and L. A. Carlsen,

    “Improved Kick Management During MPD by Real-Time Pore-Pressure Estimation,” SPE Drilling & Completion, 25(4): 577-584

    , 2010
  11. Darby, M. L. and M. Nikolaou,

    “Multivariable system identification for integral controllability,” Automatica, Vol. 45 (10): 2194-2204

    , 2009
  12. W. J. Foster, N. Dowla, S. Y. Joshi, M. Nikolaou,

    “The fluid mechanics of scleral buckling surgery for the repair of retinal detachment,” Graefes Arch Clin Exp Ophthalmol, DOI 10.1007/s00417-009-1198-z

    , 2009
  13. Lim, T. P.; Ledesma, K. R.; Chang, K. T.; Hou, J. G.; Kwa, A. L.; Nikolaou, M.; Quinn, J. P.; Prince, R. A.; Tam, V. H.,

    “Quantitative assessment of combination antimicrobial therapy against multidrug-resistant Acinetobacter baumannii,” Antimicrobial Agents And Chemotherapy, 52 (8), 2898-2904

    , 2008
  14. Tam, V. H.; Ledesma, K. R.; Vo, G.; Kabbara, S.; Lim, T. P.; Nikolaou, M.,

    “Pharmacodynamic Modeling of Aminoglycosides against Pseudomonas aeruginosa and Acinetobacter baumannii: Identifying Dosing Regimens To Suppress Resistance Development,” Antimicrobial Agents And Chemotherapy, 52 (11), 3987-3993

    , 2008
  15. Darby, M. L., and M. Nikolaou,

    “A Parametric Programming Approach to Moving Horizon State Estimation,” Automatica, 43 (5): 885-891

    , 2007
  16. Nikolaou M, Schilling AN, Vo G, et al.,

    “Modeling of microbial population responses to time-periodic concentrations of antimicrobial agents,” Annals of Biomedical Engineering, 35 (8): 1458-1470

    , 2007
  17. Tam, V. H.; Schilling, A. N.; Poole, K.; Nikolaou, M.,

    “Mathematical modelling response of Pseudomonas aeruginosa to meropenem,” Journal Of Antimicrobial Chemotherapy, 60 (6), 1302-1309

    , 2007
  18. Tam, V. H.; Vo, G.; Kabbara, S.; Nikolaou, M.,

    “Pharmacodynamics of gentamicin against Pseudomonas aeruginosa: modelling bacterial response to drug-selective pressures,” International Journal Of Antimicrobial Agents, 29, S87-S88

    , 2007
  19. L. Saputelli, M. Nikolaou b, and M.J. Economides,

    “Real-Time Reservoir Management: A Multi-Scale Adaptive Optimization and Control Approach,” J. Computational Geosciences, invited publication for Special Issue on Closed-Loop Reservoir Management, 10, 61-96

    , 2006
  20. M. Nikolaou and V. H. Tam,

    “A new modeling approach to the effect of antimicrobial agents on heterogeneous microbial populations,” Journal of Mathematical Biology, vol. 52, pp. 154-182

    , 2006
  21. Nikolaou, M.,

    “Control of Snack Food Manufacturing Systems: Potato chips and micro-chips are more similar than commonly believed,” IEEE Control Systems Magazine, special issue on process control, 26 (4): 40-54

    , 2006
  22. L. Saputelli, M. Nikolaou, and M. J. Economides,

    “Self-learning reservoir management,” SPE Reservoir Evaluation & Engineering, vol. 8, pp. 534-547

    , 2005
  23. M. Nikolaou, P. Misra, V. H. Tam, and A. D. Bailey,

    “Complexity in semiconductor manufacturing, activity of antimicrobial agents, and drilling of hydrocarbon wells: Common themes and case studies,” Computers & Chemical Engineering, vol. 29, pp. 2266-2289

    , 2005
  24. V. H. Tam and M. Nikolaou,

    “Mathematical modelling of resistance emergence,” Journal Of Antimicrobial Chemotherapy, vol. 56, pp. 983-983

    , 2005
  25. V. H. Tam, A. N. Schilling, and M. Nikolaou,

    “Modelling time-kill studies to discern the pharmacodynamics of meropenem,” Journal Of Antimicrobial Chemotherapy, vol. 55, pp. 699-706

    , 2005
  26. Misra P, Nikolaou M,

    “Input design for model order determination in subspace identification,” AICHE J, 49 (8): 2124-2132

    , 2003
  27. Nikolaou M, Misra P,

    “Linear control of nonlinear processes: recent developments and future directions,” Comput. Chem. Eng., 27 (8-9): 1043-1059

    , 2003
  28. Eker, S. A., and M. Nikolaou,

    “Linear Control of Nonlinear Systems - The Interplay between Nonlinearity and Feedback,” AIChE J., 48 (9): 1957-1980

    , 2002
    Link to file
  29. Shouche, M., H. Genceli, and M. Nikolaou,

    “Dependence of Model Predictive Control and Identification Performance on On-Line Optimization Techniques,” Computers Chem. Engng., 26, 9, 1241-1252

    , 2002
  30. Zhang, H., Y. Peng, M. Nikolaou,

    “Development of a Data Driven Dynamic Model for a Plasma Etching Reactor,” J. Vac. Sci. Tech. B, 20 (3): 891-901

    , 2002
    Link to file
  31. 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
    Link to file
  32. Schwarm, A., and M. Nikolaou,

    “Chance Constrained Model Predictive Control,” AIChE Journal, 45, 8, 1743-1752

    , 1999
    Link to file
  33. 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
  34. Nikolaou, M.,

    “Identification and Adaptive Control,” Comp. Chem. Eng., special issue on NSF/NIST Vision 2020 Workshop, 23/2, pp. 215 - 225

    , 1998
  35. Nikolaou, M., and P. Vuthandam,

    “FIR Model Identification: Achieving Parsimony through Kernel Compression with Wavelets,” AIChE J., 44, No. 1, 141-150

    , 1998
    Link to file
  36. Nikolaou, M., and V. Hanagandi,

    “Nonlinearity Quantification and its Application to Nonlinear System Identification,” Chem. Eng. Comm., 166, 1-33

    , 1998
    Link to file
  37. 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
    Link to file
  38. Vuthandam, P., and M. Nikolaou,

    “Constrained Model Predictive Control and Identification: A Weak Persistent Excitation Approach,” AIChE J., 43, 9, 2279-2288

    , 1997
  39. Genceli, H., and M. Nikolaou,

    “New Approach to Constrained Predictive Control with Simultaneous Model Identification,” AIChE J., 42, 10, 2857-2869

    , 1996
  40. 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
  41. Moridis, G. J., M. Nikolaou, and Y. You,

    “The Use of Wavelet Transforms in the Solution of Two-Phase Flow Problems,” SPE J., 29144, 169-178

    , 1996
  42. Sarimveis, H., H. Genceli, and M. Nikolaou,

    “Design of Robust Non-Square Constrained Model Predictive Control,” AIChE J., 42, 9, 2582-2593

    , 1996
  43. Genceli, H. and M. Nikolaou,

    “Design of Robust Constrained Nonlinear Model Predictive Controllers with Volterra Series,” AIChE J., 41, 9, 2098-2107

    , 1995
  44. Nikolaou, M., and V. Hanagandi,

    “Recurrent Neural Networks in Decoupling Control of Multivariable Nonlinear Systems,” Chem. Eng. Communications, 136, 201-216

    , 1995
  45. Vuthandam, P., H. Genceli, and M. Nikolaou,

    “Performance Bounds of Robust Model-Predictive Control,” AIChE J., 41, 9, 2083-2097

    , 1995
  46. 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
  47. 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
  48. 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
    Link to file
  49. You, Y., and M. Nikolaou,

    “Dynamic Process Modeling with Recurrent Neural Networks,” AIChE J., 39, 10, 1654-1667

    , 1993
  50. Genceli, H., and M. Nikolaou,

    “Robust Stability Analysis of Constrained l1-Norm Model Predictive Control,” AIChE J., 39, 12, 1954-1965

    , 1993
  51. Nikolaou, M. and V. Manousiouthakis,

    “Sensitivity Analysis of Optimal Control Policies for Batch Processes,” Chemical Engineering Communications, 97, 27-45

    , 1990
  52. Manousiouthakis, V. and M. Nikolaou,

    “Analysis of Decentralized Control Structures for Nonlinear Systems,” AIChE Journal, 35, 4, 549-558

    , 1989
  53. Nikolaou, M. and V. Manousiouthakis,

    “A Hybrid Approach to Nonlinear System Stability and Performance,” AIChE Journal, 35, 4, 559-572

    , 1989

Books

  1. 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
    Link to file
  2. Nikolaou, M.,

    “Model Predictive Controllers: A Critical Synthesis of Theory and Industrial Needs,” Advances in Chemical Engineering Series, Academic Press

    , 2001
    Link to file
  3. Hanagandi, V., and M. Nikolaou,

    “Applications of Genetic Algorithms in Chemical Engineering,” Practical Handbook of Genetic Algorithms, Lance Chambers Ed., Vol. 2, 221-252, CRC Press

    , 1995
  4. 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

Conference Proceedings Publications

  1. Nikolaou, M.,

    “Computer-Aided Process Engineering in Oil and Gas Production,” CPC VIII

    , 2012
  2. Breyholtz, O., G. Nygaard and M. Nikolaou,

    “Automatic Control of Managed Pressure Drilling,” 2010 American Control Conference, 442-447

    , 2010
  3. A. Awasthi, S. Sankaran, M. Nikolaou, L. Saputelli, & G. Mijares,

    “Short-Term Production Optimization by Automated Adaptive Modeling and Control,” SPE 112239-MS

    , 2008
  4. A. Awasthi, S. Sankaran, M. Nikolaou, L. Saputelli, and G. Mijares,

    “Meeting the Challenges of Real-Time Production Optimization: A Parametric Model-Based Approach,” SPE 111853-MS

    , 2008
  5. L. A. Carlsen, G. Nygaard, J. E. Gravdal, M. Nikolaou, J. Schubert,

    “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

    , 2008
  6. A. Awasthi, S. Sankaran, M. Nikolaou, L. Saputelli and G. Mijares,

    “Closing the Gap Between Reservoir Modeling and Production Optimization,” SPE 107463-MS

    , 2007
  7. Ankur Awasthi, Sathish Sankaran, Michael Nikolaou, Luigi Saputelli, and Gerardo Mijares,

    “Closing the Gap Between Reservoir Modeling and Production Optimization,” SPE 107463-MS

    , 2007
  8. M. Nikolaou, A.S. Cullick and L. Saputelli,

    “Production Optimization—A Moving-Horizon Approach,” SPE 99358-MS

    , 2006
  9. 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
  10. L. Saputelli, M. Economides, M. Nikolaou, V. Kelessidis,

    “Real-time Decision-making for Value Creation while Drilling,” SPE 85314-MS

    , 2003
  11. L. Saputelli, M. Nikolaou, M.J. Economides,

    “Self-Learning Reservoir Management,” SPE 84064-MS

    , 2003
  12. 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
  13. Nikolaou, M., and A. D. Bailey, III,

    “Application of reduced-rank multivariate methods to the monitoring of spatial uniformity of wafer etching,” MASM

    , 2002
    Link to file
  14. Sathish Sankaran, Wolfgang Deeg, Michael Nikolaou, Michael J. Economides,

    “Measurements and Inverse Modeling for Far-Field State of Stress Esimation,” SPE 71647-MS

    , 2001
  15. 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
  16. Zhang, H., and M. Nikolaou,

    “Control of Spatial Uniformity in Microelectronics Manufacturing: An Integrated Approach,” APC/AEC XII Sematech Workshop, Lake Tahoe

    , 2000
    Link to file
  17. 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
  18. Nikolaou, M., and D. Mantha,

    “Efficient nonlinear modeling using wavelets and related compression techniques,” NSF Workshop on Nonlinear Model Predictive Control, Ascona, CH

    , 1998
  19. Genceli, H., and M. Nikolaou,

    “A new approach to model predictive control and identification,” 1996 IFAC World Congress Proceedings, San Francisco

    , 1996
  20. Genceli, H., and M. Nikolaou,

    “A New Approach to Constrained Predictive Control with Simultaneous Model Identification,” European Symposium on Computer-Aided Process Engineering Proceedings, Rhodes, Greece

    , 1996
  21. Nikolaou, M.,

    “Computer-Aided Process Engineering in the Snack Food Industry,” CPC V preprints, Tahoe City, CA

    , 1996
  22. Nikolaou, M.,

    “Directions in Computer-Aided Process Engineering,” AIChE World Congress Proceedings, San Diego, CA

    , 1996
  23. Nikolaou, M., and B. Joseph,

    “Intelligent Control,” ISPE 95 Proceedings, 68-69

    , 1996
  24. Sarimveis, H., H. Genceli, and M. Nikolaou,

    “Design of Robust Non-Square Constrained Model Predictive Control,” European Symposium on Computer-Aided Process Engineering Proceedings, Rhodes, Greece

    , 1996
  25. Hanagandi, S. Brown, R. Sherman, R. Jones, and M. Nikolaou,

    “Control Strategies for the TSTA Distillation Column I,” ACC Proceedings, 2653-2656

    , 1995
  26. 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
  27. 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
  28. Nikolaou, M.,

    “The 2-norm for Nonlinear Processes: Application to Modeling and Control Problems,” PSE’94 Proceedings, Kyongju, KOREA

    , 1994
  29. Nikolaou, M.,

    “Teaching Numerical Methods Using Interactive Computer Spreadsheets in Class,” Proceedings of ASEE Annual Conference, Session 3162, 2731-2736, Edmonton, Canada

    , 1994
  30. Vuthandam, P., H. Genceli, and M. Nikolaou,

    “Analysis and Synthesis Methods for Robust Model Predictive Control,” ADCHEM’94 Proceedings, Kyoto, JAPAN

    , 1994
  31. 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
  32. Nikolaou, M.,

    “When is Nonlinear Dynamic Modeling Necessary?,” ACC Proceedings, 910-914, San Francisco, CA

    , 1993
  33. Nikolaou, M.,

    “Neural Network Modeling of Nonlinear Dynamical Systems,” ACC Proceedings, 1460-1464, San Francisco, CA

    , 1993
  34. 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
  35. Nikolaou, M., and H. Sarimveis,

    “Process Modeling with Recurrent Neural Networks,” ANNIE 91 Proceedings

    , 1991
  36. 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
  37. 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
  38. Nikolaou, M. and V. Manousiouthakis,

    “Robust Control of Batch Processes,” Proceedings of the American Control Conference, Atlanta, GA, 665-670

    , 1988
  39. 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
  40. Manousiouthakis, V. and M. Nikolaou,

    “On the Nonlinear Block Relative Gain,” Proceedings of the American Control Conference, Seattle, WA, 2120-2125

    , 1987
  41. 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

Major Reports

  1. 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
    Link to file

Patents

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