“Modeling, Identification and Control at Telemark University College”

Authors: Bernt Lie, David Di Ruscio, Rolf Ergon, Bjørn Glemmestad, Maths Halstensen, Finn Haugen, Saba Mylvaganam, Nils-Olav Skeie and Dietmar Winkler,
Affiliation: Telemark University College
Reference: 2009, Vol 30, No 3, pp. 133-147.

Keywords: modeling, simulation, identification, control, sensor technology

Abstract: Master studies in process automation started in 1989 at what soon became Telemark University College, and the 20 year anniversary marks the start of our own PhD degree in Process, Energy and Automation Engineering. The paper gives an overview of research activities related to control engineering at Department of Electrical Engineering, Information Technology and Cybernetics.

PDF PDF (1287 Kb)        DOI: 10.4173/mic.2009.3.4

DOI forward links to this article:
[1] Yan Ru, Chaminda Pradeep and Saba Mylvaganam (2011), doi:10.1088/0957-0233/22/10/104006
References:
[1] Aaker, O. (1996). Operator Support and Diagnostic Reasoning in an Industrial Process, Ph.D. thesis, NTNU, Porsgrunn, NTNU-HiT, 82-7119-976-5, 0802-3271.
[2] Alic, M., Hauge, T. A., Lie, B. (2009). Developing A Simple Modelica Library For Simulation of The Xstrata Nikkelverk Copper Production Plant, In Dong Energy, editor, Proc. 50th Scand. Conf. on Simulation and Modeling.SIMS. Fredericia, Denmark.
[3] Alme, K. J. (2006). Artificial Neural Network for Direct Parameter Estimation in Electrical Capacitance Tomography, In Protocom. Warsawa.
[4] Alme, K. J. (2007). Material Distribution and Interface Detection Using EIT, Ph.D. thesis, NTNU-HiT, Porsgrunn, 2007:223, ISBN 978-82-471-4929-3 (printed), 978-82-471-4932-0 (elec.), ISSN 1503-8181.
[5] Alme, K. J. Mylvaganam, S. (2006). Conductivity Effects in Electrical Tomography Systems with focus on 3D Effects Using COMSOL Multiphysics Modules, In Comsol Multiphysics Conf. Copenhagen.
[6] Alme, K. J. Mylvaganam, S. (2006). Electrical Capacitance Tomography - Sensor Models, Design, Simulations and Experimental Verification, IEEE Sensors Journal, .5:1256-1266 doi:10.1109/JSEN.2006.881409
[7] Alme, K. J. Mylvaganam, S. (2007). Comparison of Different Measurement Protocols in Electrical Capacitance Tomography Using Simulations, IEEE Trans. on Instr. and& Meas., 5.6:2119-2130.
[8] Aoki, M. (1987). State Space Modeling of Time Series, Springer-Verlag Berlin Heidelberg.
[9] Chai, Q. (2008). Modeling, Estimation, and Control of Biological Wastewater Treatment Plants, Ph.D. thesis, NTNU-HiT, Porsgrunn, 2008:108, ISBN 978-82-471-8155-3, 978-82-471-8169-0, ISSN 1503-8181.
[10] Chai, Q. Lie, B. (2008). Predictive Control of an Intermittently Aerated Activated Sludge Process, American Control Conference, June:11-13. Seattle, USA.
[11] Dahlquist, E. (2008). Use of Modeling and Simulation in Pulp and Paper Industry, http://works.bepress.com/dr_erik_dahlquist. ISBN-977493-0-5.
[12] Damslora, A. J. (1998). Optimisation Based Control of Batch Emulsion Polymerisation of Vinyl Chloride, Ph.D. thesis, NTNU-HiT, Porsgrunn, Thesis 1998:29, ISBN 82-471-0224-2.
[13] Damslora, A. J., Lie, B., Sælid, S. (1998). Reduction of PVC Batch Time by Optimal Control of Free Radical Concentration, Nonlinear Model Based Control, 353:781-803. Kluwer, The Netherlands.
[14] Datta, U. (2007). Multimodal Measurements in Dilute Phase Pneumatic Conveying Systems, Ph.D. thesis, NTNU-HiT, 2007:240, ISBN 978-82-471-5322-2 (printed), 978-82-471-5336-9 (elec.), ISSN 1503-8181.
[15] Datta, U., Dyakowski, T., Mylvaganam, S. (2007). Average Particle Size and Instantaneous Mass Flow Rate Estimation in Dilute Phase Pneumatic Conveying Systems using ECT, In 5th World Congress on Industrial Process Tomography. Bergen.
[16] Datta, U., Dyakowski, T., Mylvaganam, S. (2007). Estimation of Particulate Velocity Components in Pneumatic Transport Using Pixel Based Correlation with Dual Plane ECT, Chemical Engineering Journal, 13.2/3:87-99 doi:10.1016/j.cej.2006.08.034
[17] Datta, U., Mathiesen, V., Mylvaganam, S. (2003). Tomometric Approach using Multi Sensor Data Fusion in Particle Segregation Studies, In 3rd World Cong. on Industrial Process Tomography. Banff, Canada.
[18] Di Ruscio, D. (1994). Methods for the Identification of State Space Models from Input and Output Measurements, In SYSID 94, The 10th IFAC Symposium on System Identification. Copenhagen.
[19] Di Ruscio, D. (1996). Combined Deterministic and Stochastic System Identification and Realization: DSR - a Subspace Approach Based on Observations, Modeling, Identification and Control, 1.3:193-230 doi:10.4173/mic.1996.3.3
[20] Di Ruscio, D. (2000). A Weighted View of the Partial Least Squares Algorithm, Automatica, 36:831-850 doi:10.1016/S0005-1098(99)00210-1
[21] Di Ruscio, D. (2003). Subspace System Identification of the Kalman Filter, Modeling, Identification and Control, 2.3:125-157 doi:10.4173/mic.2003.3.1
[22] Di Ruscio, D. (2008). Subspace System Identification of the Kalman Filter: Open and Closed Loop Systems, In Proc. of the Intl. Multi-Conference on Engineering and Technological Innovation. Orlando, USA.
[23] Duenas Diez, M. (2004). Population Balance Modeling and Passivity-based Control of Particulate Processes, Applied to the Silgrain, Ph.D. thesis, NTNU-HiT, Porsgrunn, 2004:35, ISBN 82-471-6276-8 (printed), 82-471-6274-1 (elec.), ISSN 1503-8181.
[24] Duenas Diez, M., Fjeld, M., Andersen, E., Lie, B. (2006). Validation of a Compartmental Population Balance Model of an Industrial Leaching Process: The Silgrain Process, Chemical Engineering Science, 6.1:229-245 doi:10.1016/j.ces.2005.01.047
[25] Duenas Diez, M., Ydstie, B. E., Fjeld, M., Lie, B. (2008). Inventory Control of Particulate Processes, Computers and Chemical Engineering, 32:46-67 doi:10.1016/j.compchemeng.2007.01.007
[26] Ergon, R. (1999). Dynamic System Multivariate Calibration for Optimal Primary Output Estimation, Ph.D. thesis, NTNU, Trondheim, 1999:72, NTNU-HiT, ISBN 82-471-0442-3, ISSN 0802-3271.
[27] Ergon, R. (1999). On primary output estimation by use of secondary measurements as input signals in system identification, IEEE Trans. Autom. Control, 4.4:821-825 doi:10.1109/9.754826
[28] Ergon, R. (2002). Noise handling capabilities of multivariate calibration models, Modeling, Identification and Control, 23:259-273 doi:10.4173/mic.2002.4.2
[29] Ergon, R. (2002). PLS score-loading correspondence and a biorthogonal factorization, J. Chemometrics, 1.7:368-373 doi:10.1002/cem.736
[30] Ergon, R. (2003). Compression into two-component PLS factorization, J. Chemometrics, 1.6:303-312 doi:10.1002/cem.803
[31] Ergon, R. (2004). Informative PLS score-loading plots for process understanding and monitoring, Process Control. 1.8:889-897 doi:10.1016/j.jprocont.2004.02.004
[32] Ergon, R. (2005). PLS post-processing by similarity transformation (PLS+ST): A simple alternative to 0-PLS, Journal of Chemometrics. 19(1):1-4 doi:10.1002/cem.899
[33] Ergon, R. (2006). Reduced PCR/PLSR models by subspace projection, Chemom. Intell. Lab. Syst. 8.1:68-73 doi:10.1016/j.chemolab.2005.09.008
[34] Ergon, R. (2007). Finding Y-relevant part of X by use of PCR and PLSR model reduction methods, Journal of Chemometrics, 21:537-546 doi:10.1002/cem.1062
[35] Ergon, R. (2009). Informative score-loading-contribution plots for multi-response process monitoring, Chemom. Intell. Lab. Syst., 9.1:31-34 doi:10.1016/j.chemolab.2008.08.001
[36] Ergon, R. (2009). Re-interpretation of NIPALS results solves PLSR inconsistency problem, Journal of Chemometrics, 23:72-75 doi:10.1002/cem.803
[37] Ergon, R. Di Ruscio, D. (1997). Dynamic system calibration by system identification methods, In Fourth European Control Conf..ECC 97. Brussels.
[38] Ergon, R. Halstensen, M. (2001). Dynamic system multivariate calibration based on multirate sampling data, Modeling, Identification and Control, 2.2:73-88 doi:10.4173/mic.2001.2.2
[39] Esbensen, K. (2001). Multivariate Analysis - in practice, Camo AS, Oslo, 5th edition.
[40] Esbensen, K. H., Halstensen, M., Lied, T. T., Saudland, A., Svalestuen, J., de Silva, S., Hope, B. (1998). Acoustic chemometrics - from noise to information, Chemom. Intell. Lab. Sys., 44:61-76 doi:10.1016/S0169-7439(98)00114-2
[41] Esbensen, K. H., Hope, B., Lied, T. T., Halstensen, M., Sundberg, K., Gravermoen, T. (1999). Acoustic chemometrics for fluid flow quantifications -II: A small constriction will go a long way, Journal of Chemometrics, 13:209-236.
[42] Furenes, B. (2009). Model Based Control of Solidification, Ph.D. thesis, NTNU-HiT, 2009:228, ISBN-471-1860-3, 978-82-471-1861-0, ISSN 1503-8181.
[43] Glemmestad, B. (1997). Optimal Operation of Integrated Processes, Studies on heat recovery systems, Ph.D. thesis, NTNU-HiT, 1997:118, ISBN 82-471-0156-4, ISSN 0802-3271.
[44] Glemmestad, B., Ertler, G., Hillestad, M. (2002). Advanced Process Control in a Borstar PP Plant, In Proc. from ECOREP II. Lyon, pp. 46-49.
[45] Glemmestad, B. Hillestad, B. (2001). Experience from an Industrial MPC Implementation, In NPC10. NPC, Åbo, Finland, pp. 77-78.
[46] Glemmestad, B., Hofsten, K., Wilsher, E., Andersen, K. S. (2004). Non-Linear Model Predictive Control of Polyolefin Plants, In NPC12. n/a, Gothenburg, Sweden, pp. 66-67.
[47] Golub, G. Kahan, W. (1965). Calculating the singular values and pseudo-inverse of a matrix, SIAM J. Numer. Anal., 2:205-224.
[48] Golub, G. H. Van Loan, C. F. (1986). Matrix Computations, North Oxford Academic, London.
[49] Halstensen, M. Acoustic Chemometrics. (2001). Experimental multivariate sensor technology and development of system prototypes for industrial multi-phase characterisation: selected forays, Ph.D. thesis, NTNU-HiT, 2001:111, ISBN 82-471-5381-5, ISSN 0809-103X.
[50] Halstensen, M., de Bakker, P., Esbensen, K. H. (2006). Acoustic chemometric monitoring of an industrial granulation production process - a PAT feasibility study, Chemom. Intell. Lab. Syst., 84:88-97 doi:10.1016/j.chemolab.2006.05.012
[51] Halstensen, M. Esbensen, K. H. (2000). New developments in acoustic chemometric prediction of particle size distribution - the problem is the solution, Journal of Chemometrics, 14:463-481.
[52] Halstensen, M., de Silva, S., Esbensen, K. H. (1998). Acoustic monitoring of pneumatic transport lines - from noise to information, KONA Powder and Particle, 16:170-178.
[53] Hauge, T. A. (2003). Roll-out of Model Based Control with Application to Paper Machines, Ph.D. thesis, NTNU, 2003:31, ISBN 82-471-5581-8, ISSN 0809-103X.
[54] Hauge, T. A., Slora, R., Lie, B. (2005). Application and roll-out of infinite horizon MPC employing a nonlinear mechanistic model to paper machines, Journal of Process Control, 1.2:201-213 doi:10.1016/j.jprocont.2004.05.003
[55] Haugen, F. (2005). Introduction to LabVIEW Control Design, System Identification and Simulation Tools, In National Instruments Days. Drammen, Norway.
[56] Haugen, F. (2008). Examples of Student Assignments on Modeling, Simulation, and Control, In National Instruments Days. Drammen, Norway.
[57] Haugen, F. (2009). Air Heater, Technical report, Telemark University College, http://home.hit.no/~finnh/air_heater.
[58] Haugen, F. (2009). Basic Dynamics and Control, TechTeach, ISBN 978-82-91748-13-9.
[59] Haugen, F. (2009). Lab assignment: Hardware-in-the-loop, HIL simulation. http://www2.hit.no/tf/fag/sce2006/2009/hil_sim.
[60] Haugen, F. (2009). Lab assignment: Implementation of a control system, http://www2.hit.no/tf/fag/sce1106/2009/project/project.
[61] Haugen, F. (2009). Lab assignment: Model-based predictive control, MPC. http://www2.hit.no/tf/fag/scev3106/2009/projects/mpc.
[62] Haugen, F. (2009). Lab assignment: Soft-sensor, state estimator. http://www2.hit.no/tf/fag/sce4206/2009/softsensor.
[63] Haugen, F. (2009). Lab assignment: System identification, http://www2.hit.no/tf/fag/sce4206/2009/system_ident.
[64] Haugen, F. (2009). Lecture Notes in Models, Estimation and Control, TechTeach, ISBN 978-82-91748-14-6.
[65] Haugen, F. (2009). Water Tank, Technical report, Telemark University College, http://home.hit.no/~finnh/dok_tankmodell.
[66] Haugen, F., Fjelddalen, E., Edgar, T., Dunia, R. (2007). Examples of Student Assignments on Modeling, Simulation, and Control, CACHE News.Computer Aids for Chemical Engineering, Winter.
[67] Haugen, F., Fjelddalen, E., Edgar, T., R. Dunia. (2008). A Complete Programming Framework for Process Control Education, In 2nd IEEE Multi-conference on Systems and Control. IEEE, San Antonio.
[68] Haugwitz, S., Wilsher, E., Hofsten, K., Andersen, K. S., Glemmestad, B. (2008). Commissioning of Nonlinear Model Predictive Controllers to a New-Polypropylene Plant, In Reglermötet. Sweden.
[69] Hestenes, M. R. Stiefel, E. (1952). Methods for Conjugate Gradients for Solving Linear Systems, J. of Res. of the national Bureau of Stand., 4.6:409-436.
[70] Ho, B. L. Kalman, R. E. (1966). Effective construction of linear state-variable models from input/output functions, Regelungstechnik, 1.12:545-592.
[71] Huang, J. (2001). Developments in Applied Chemometrics AMT, acoustic chemometrics and N-way image analysis, Ph.D. thesis, NTNU-HiT, Porsgrunn, 2001:25, ISBN 82-7984-187-3, ISSN 0809-103X.
[72] Komperød, M., Bones, J. A., Lie, B. (2009). Solution to an Implementation Issue for a Two-Step ARX Algorithm, with Application to the Czochralski Crystallization Process, In Proc. 50th Scand. Conf. on Simulation and Modeling. Fredericia.
[73] Lie, B. (1990). Control Structures for Polymerization Processes Applied to Polypropene Manufacturing, Ph.D. thesis, NTNU, Trondheim, Report 82-W.
[74] Lie, B. (1995). Attainable Performance in LQG Control, Methods of Model Based Process Control. 293:263-295. Kluwer Academic Publishers.
[75] Lie, B. (2009). Model Uncertainty and Control Consequences: a Paper Machine Study, Mathematical and Computer Modelling of Dynamical Systems. 1.5:463-477 doi:10.1080/13873950903375452
[76] Lie, B., Duenas Diez, M., Hauge, T. A. (2005). A Comparison of Implementation Strategies for MPC, Modeling, Identification and Control. 2.1:39-50 doi:10.4173/mic.2005.1.3
[77] Lie, B. Hauge, T. A. (2008). Modeling of an Industrial Copper Leaching and Electrowinning Process, with Validation Against Experimental Data, In Proc. 49th Scand. Conf. on Simulation and& Modeling. Oslo.
[78] Lie, B. Heath, W. (2008). Model Based Control, In E. Dahlquist, editor, Use of Modeling and Simulation in Pulp and Paper Industry. pp. 978-91. http://works.bepress.com/dr_erik_dahlquist, COST Office, ISBN-977493-0-5.
[79] Lied, T. T. (2000). Multivariate Image Regression, MIR for Quantitative Predictions. Ph.D. thesis, NTNU-HiT, 2000:99, ISBN 82-7984-126-1, ISSN 0809-103X.
[80] Lorentzen, H., Timmerberg, J., Mylvaganam, S. (2008). Calculation of Cable Parameters for Different Cable Shapes, In European COMSOL Conf.
[81] Lundhaug, M. (2002). Sea Ice Studies in the Northern Sea Route by Use of Synthetic Aperture Radar, Ph.D. thesis, NTNU-HiT, Porsgrunn, 2002:22, ISBN 82-471-5414-5, ISSN 0809-103X.
[82] Martens, H. Næs, T. (1989). Multivariate Calibration, John Wiley and Sons Ltd.
[83] Modelica-Association. (2009). Modelica - A Unified Object-Oriented Language for Physical Systems Modeling - Language Specification, Modelica Association, version 3.1 edition. http://www.modelica.org.
[84] Modelica.org. (2009). Tools page on Modelica, org. http://www.modelica.org/tools.
[85] Mylvaganam, S. (2003). Some Applications of Acoustic Emission in Particle Science and Technology, Particulate Science and Technology, 2.3:293-301 doi:10.1080/02726350307485
[86] Mylvaganam, S., Datta, U., Halstensen, M., Mathiesen, V. (2003). Multi Sensor Suite Comprising Active and Passive Transducers for Monitoring Solids Flow and Silo Integrity, In IEEE UFFC Symp. Honolulu.
[87] Mylvaganam, S. Dyakowski, T. (2005). Estimating transverse velocity components of slug flow using pixel by pixel correlation method using ECT, In 4th World Cong. Ind. Proc. Tomography. Aizu, pp. 5-8.
[88] Nilsen, G. W. (2005). Topics in Open and Closed Loop Subspace System Identification: Finite Databased Methods, Ph.D. thesis, NTNU-HiT, 2005:228, ISBN-7357-3, 82-471-7356-5, ISSN 1503-8181.
[89] Nygaard, G., Nævdal, G., Mylvaganam, S. (2006). Evaluating Nonlinear Kalman Filters for Parameter Estimation in Reservoirs During Petroleum Well Drilling, In IEEE Conference on Control Applications. München, Germany, pp. 4-6.
[90] Nygaard, G. H. Nævdal, G. (2006). Non-linear model predictive control scheme for stabilizing annulus pressure during oil well drilling, Journal of Process Control, 1.7:719-732 doi:10.1016/j.jprocont.2006.01.002
[91] Nygaard, G. H., Vefring, E. H., Fjelde, K.-K., Nævdal, G., Lorentzen, R. J., Mylvaganam, S. (2007). Bottomhole Pressure Control during Drilling Operations in Gas-Dominant Wells, SPE Journal, 1.1:49-61 doi:10.2118/91578-PA
[92] Nygaard, G. H., Vefring, E. H., Lorentzen, R. J., Nævdal, G., Fjelde, K. K., Mylvaganam, S. (2004). Bottomhole pressure control during pipe connection in gas-dominant wells, In SPE/IADC Underbalanced Tech. Conf. and Exhibition. Houston.
[93] Nygaard, G. H., Vefring, E. H., Mylvaganam, S., Lorentzen, R. J., Nævdal, G., Fjelde, K. K. (2004). Underbalanced drilling: improving pipe connection procedures using automatic control, In SPE Ann. Tech. Conf. and Exh. Conv. Center, Houston.
[94] Nygaard, O. G. H. (2006). Multivariable Process Control in High Temperature and High Pressure Environment Using Non-intrusive Multi Sensor Data Fusion, Ph.D. thesis, NTNU-HiT, 2006:38, ISBN 82-471-7820-6, 82-471-7819-2, ISSN 1503-8181.
[95] Pell, R., Ramos, L., Manne, R. (2007). The model space in partial least squares regression, Journal of Chemometrics, 21:165-172 doi:10.1002/cem.1067
[96] Qin, S. J. Ljung, L. (2003). Closed-loop Subspace Identification with Innovation Estimation, In Proc. of the 13th IFAC SYSID Symposium. pp. 887-892.
[97] Qin, S. J., Weilu, L., Ljung, L. (2005). A Novel Subspace Approach with Enforced Causal Models, Automatica, 41:2043-2053 doi:10.1016/j.automatica.2005.06.010
[98] Sarmiento Ferrero, C., Chai, Q., Duenas Diez, M., Amrani, S. H., Lie, B. (2006). Systematic Analysis of Parameter Identifiability for Improved Fitting of a Biological Wastewater Model to Experimental Data, Modeling, Identification and Control, 2.4:219-238 doi:10.4173/mic.2006.4.2
[99] Skeie, N.-O. (2008). Soft Sensors for Level Estimation, Ph.D. thesis, NTNU-HiT, Porsgrunn, 2008:102, ISBN 978-82-471-4462-6, 978-82-471-4476-3, ISSN 1503-8181.
[100] Skeie, N.-O. Lie, B. (2006). Level and Interface Estimation in an Oil / Water Separator Using Multi Sensor Data Fusion, in E, In E. Juuso, editor, 47th Conf. on Simulation and Modelling. pp. 210-215.
[101] Skeie, N.-O., Mylvaganam, S., Lie, B. (2006). Using Multi Sensor Data Fusion for Level Estimation in a Separator, in W, In 16th European Symp. on Comp. Aided Proc. Engn. and 9th Intl. Symp. on Proc. Sys. Engn., volume 21. Elsevier, pp. 1383-1388.
[102] Sotomayor, O. A. Z., Parka, S. W., Garcia, C. (2003). Multivariable Identification of an Activated Sludge Process with Subspace-based Algorithms, Control Engineering Practice, 11:961-969 doi:10.1016/S0967-0661(02)00210-1
[103] Timmerberg, J., Beckmann, P., Mylvaganam, S. (2009). Quasianalytical Estimates of Inductance Using Subconductor Methods, In Intern. Conference: Environment, Technology, Resources. Rezekne, Latvia.
[104] Trygg, J. Wold, S. (2002). Orthogonal projections to latent structures, O-PLS. J. Chemometrics. 16:119-128 doi:10.1002/cem.695
[105] Vefring, E. H., Nygaard, G. H., Fjelde, K. K., Rolf, Lorentzen, J., Nævdal, G., Merl, A. (2002). Reservoir Characterization During Underbalanced Drilling: Methodology, Accuracy, and Necessary Data, In Proc. SPE Ann. Tech. Conf. San Antonio.
[106] Videla, J. I. Lie, B. (2006). A New Energy Building Simulation Library, In C. Kral and A. Haumer, editors, Proc. of the 5th Intl. Modelica Conference. The Modelica Association, Vienna, pp. 685-693.
[107] Videla, J. I. Lie, B. (2008). Model Reduction of a Micro ICE Based CHP Model, In 1st Intl. Conf./Works. in Micro-Cogeneration Techn. and Appl.
[108] Viumdal, H., Ru, B., Y.and Moxnes, Liane, S., M. an Mylvaganam. (2010). Multi sensor data fusion for aluminium cell health monitoring and control, In TMS annual meeting Proceedings CD. Seattl.
[109] Wærstad, H., Cortvriend, L., Datta, U., Mathiesen, V., Mylvaganam, S. (2002). Multi Sensor Data Fusion With Flange Mounted Acoustic Emission Sensors In The Monitoring Of Fluidised Beds, In IEEE UFFC Symposium. Munich, Germany.
[110] Winkler, D. Gühmann, C. (2008). Simulation of Electric Drives using freeFOClib, In Proc. of IEEE Intl. Conf. on Sustainable Energy Tech. IEEE, SMU Conf. Centre, Singapore doi:10.1109/ICSET.2008.4747173
[111] Winkler, D. Gühmann, C. (2009). Simulation of Faults in Electric Drive Systems with Modelica, In Proc. MATHMOD 09 Vienna.
[112] Yahoui, A., Mouhoumed, B., Ducharne, B., Mylvaganam, S., Sixdenier, F. (2004). Diagnostic of interturn defect in three phase system by studying hysteresis magnetic harmonics signatures, In Proc. ICEM 2004, XVI Intl. Conf. On Electrical Mach.
[113] Yahoui, H. Mylvaganam, S. (2009). Modelling and characterisation of hysteresis phenomena in 3-phase power systems for diagnostic purposes, In Symp. on Diag. for Electrical Mach., Power Elec. and Drives.
[114] Zeiger, H. McEwen, A. (1974). Approximate Linear Realizations of Given Dimensions Via Ho´s Algorithm, In IEEE Trans. on Automatic Control doi:10.1109/TAC.1974.1100525


BibTeX:
@article{MIC-2009-3-4,
  title={{Modeling, Identification and Control at Telemark University College}},
  author={Lie, Bernt and Di Ruscio, David and Ergon, Rolf and Glemmestad, Bjørn and Halstensen, Maths and Haugen, Finn and Mylvaganam, Saba and Skeie, Nils-Olav and Winkler, Dietmar},
  journal={Modeling, Identification and Control},
  volume={30},
  number={3},
  pages={133--147},
  year={2009},
  doi={10.4173/mic.2009.3.4},
  publisher={Norwegian Society of Automatic Control}
};