Dr Tim Breikin PhD
Reader in Control Engineering
Summary
Tim started his academic career in the UK as a Lecturer at the University of Manchester, in February 2004. Prior to that appointment he had nine years of research experience on the modelling, control, performance monitoring and optimisation of industrial systems.
Research
Tim's main area of research is application of advanced control techniques for industrial systems with particular emphasis on aerospace and energy generation. Tim has research experience in modelling, control, performance monitoring and optimisation of industrial systems.
He has experience in collaboration with industrial partners. In particular, he has participated in the development of a digital full authority control system for a new low fuel consumption aero engine and the design of control laws for a low emission staged combustion gas turbine engine.
Tim was also involved in a number of research projects supported by Industry, DTI, the EU INTAS programme, NATO and the Royal Society.
He has been the lead investigator on EP/C015185/1 EPSRC grant on the ‘real-time modelling for condition monitoring and performance optimisation of gas turbine engines’, and one of the leading authors of research proposal for EP/G059837/1 grant focused on energy demand reduction in paper making.
Publications
Journal articles
Palchevsky, E., Antonov, V., Filimonov, N., Rodionova, L., Kromina, L., Breikin, T., ... Koryakin, V. (2024). Development of an intelligent system for early forecasting and modelling of flood situation on the example of the Republic of Bashkortostan using a proprietary machine and deep learning library. Journal of Hydrology, 633. http://doi.org/10.1016/j.jhydrol.2024.130978
Palchevsky, E., Antonov, V., Enikeev, R.R., & Breikin, T. (2023). A system based on an artificial neural network of the second generation for decision support in especially significant situations. Journal of Hydrology, 616. http://doi.org/10.1016/j.jhydrol.2022.128844
Zhang, H., Mohamed, A., Breikin, T., & Howarth, M. (2021). Modelling and Simulation of an Ohmic Heating Process. Open Journal of Modelling and Simulation, 9 (1), 26-42. http://doi.org/10.4236/ojmsi.2021.91002
Xuewu, D., Zhiwei, G., Breikin, T., & Hong, W. (2012). High-gain observer-based estimation of parameter variations with delay alignment. IEEE Transactions on Automatic Control, 57 (3), 726-732. http://doi.org/10.1109/TAC.2011.2169635
Afshar, P., Brown, M., Austin, P., Wang, H., Breikin, T., & Maciejowski, J. (2012). Sequential modelling of thermal energy: New potential for energy optimisation in papermaking. Applied Energy, 89 (1), 97-105. http://doi.org/10.1016/j.apenergy.2011.01.022
Brown, M., Afshar, P., Wang, H., & Breikin, T. (2010). Thermal Energy Reduction in Papermaking Industries. Measurement and Control, 43 (7), 212-216. http://doi.org/10.1177/002029401004300705
Xuewu, D., Zhiwei, G., Breikin, T., & Hong, W. (2009). Zero assignment for robust H2/H[infinity] fault detection filter design. IEEE Transactions on Signal Processing, 57 (4), 1363-1372. http://doi.org/10.1109/TSP.2008.2010598
Xuewu, D., Zhiwei, G., Breikin, T., & Hong, W. (2009). Disturbance attenuation in fault detection of gas turbine engines: a discrete robust observer design. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 39 (2), 234-239. http://doi.org/10.1109/TSMCC.2008.2005845
Wang, H., & Breikin, T. (2009). Plant-Wide Optimization Using Data Driven and Knowledge Based Techniques: An Introduction. Measurement and Control, 42 (7), 203. http://doi.org/10.1177/002029400904200702
Yu, R., & Breikin, T. (2009). Hybrid Neural Network-Based Fault Diagnosis and Fault-Tolerance Design with Application in Electro-Hydraulic Servovalve. The Open Automation and Control Systems Journal, 2 (1), 62-68. http://doi.org/10.2174/1874444300902010062
Gao, Z., Dai, X., Breikin, T., & Wang, H. (2008). Novel Parameter Identification by Using a High-Gain Observer With Application to a Gas Turbine Engine. IEEE Transactions on Industrial Informatics, 4 (4), 271-279. http://doi.org/10.1109/TII.2008.2007802
Zhiwei Gao, , Breikin, T., & Hong Wang, (2008). Reliable Observer-Based Control Against Sensor Failures for Systems With Time Delays in Both State and Input. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 38 (5), 1018-1029. http://doi.org/10.1109/tsmca.2008.923050
Gao, Z., Breikin, T., & Wang, H. (2008). Discrete‐time proportional and integral observer and observer‐based controller for systems with both unknown input and output disturbances. Optimal Control Applications and Methods, 29 (3), 171-189. http://doi.org/10.1002/oca.819
Santoso, D.D., Hargrave, S.M., Breikin, T.V., Thompson, H.A., & Fleming, P.J. (2007). Diagnosis of fuel pump measurement bias in gas turbine engines. International Journal of Systems Science, 38 (8), 643-650. http://doi.org/10.1080/09528130701500422
Gao, Z., Breikin, T., & Wang, H. (2007). High-Gain Estimator and Fault-Tolerant Design With Application to a Gas Turbine Dynamic System. IEEE Transactions on Control Systems Technology, 15 (4), 740-753. http://doi.org/10.1109/tcst.2006.890282
Breikin, T.V., Herbert, I.D., Kim, S.K., Regunath, S., Hargrave, S.M., Thompson, H.A., & Fleming, P.J. (2006). Staged combustion control design for aero engines. Control Engineering Practice, 14 (4), 387-396. http://doi.org/10.1016/j.conengprac.2005.02.005
Breikin, T.V., Arkov, V.Y., & Kulikov, G.G. (2006). Application of Markov chains to identification of gas turbine engine dynamic models. International Journal of Systems Science, 37 (3), 197-205. http://doi.org/10.1080/00207720600566065
Breikin, T.V., Arkov, V.Y., & Kulikov, G.G. (2004). Regularisation approach for real-time modelling of aero gas turbines. Control Engineering Practice, 12 (4), 401-407. http://doi.org/10.1016/s0967-0661(03)00107-2
Lyantsev, O.D., Breikin, T.V., Kulikov, G.G., & Arkov, V.Y. (2004). Optimal multi-variable control of gas turbine engines. International Journal of Systems Science, 35 (2), 79-86. http://doi.org/10.1080/00207720310001657036
Lyantsev, O.D., Breikin, T.V., Kulikov, G.G., & Arkov, V.Y. (2003). On-line performance optimisation of aero engine control system. Automatica, 39 (12), 2115-2121. http://doi.org/10.1016/s0005-1098(03)00224-3
Ar'kov, V.Y., Breikin, T.V., & Kulikov, G.G. (2000). Markov simulation of dynamic objects for scaled-down tests. Journal of Computer and Systems Sciences International, 39 (2), 283-287.
Akhmetsafin, R.D., Breikin, T.V., Kulikov, G.G., & Faizullin, A.F. (1999). Identification of parameters of a control object with a delay in a closed loop. Journal of Computer and Systems Sciences International, 38 (3), 370-375.
Patel, V.C., Kadirkamanathan, V., Kulikov, G.G., Arkov, V.Y., & Breikin, T.V. (1996). Gas turbine engine condition monitoring using statistical and neural network methods. IEE Colloquium (Digest), (260).
Conference papers
Lu, Q., & Breikin, T. (2011). Fault detection for stator inter-turn short circuit in doubly fed induction generators using adaptive observers. International Journal of Advanced Mechatronic Systems, 3 (1), 44. http://doi.org/10.1504/ijamechs.2011.040162
Lu, Q., Breikin, T., & Wang, H. (2011). Modelling and fault diagnosis for DFIGs with multi-phase inter-turn short circuit. 2011 International Conference on Advanced Mechatronic Systems, ICAMechS 2011 - Final Program, 155-160.
Lu, Q., Breikin, T., & Wang, H. (2011). Modelling and Fault Diagnosis of Stator Inter-Turn Short Circuit in Doubly Fed Induction Generators. IFAC Proceedings Volumes, 44 (1), 1013-1018. http://doi.org/10.3182/20110828-6-it-1002.02217
Lu, Q., & Breikin, T. (2010). Observer based fault detection for stator inter-turn short circuit in wind turbine DFIGs. 2010 International Conference on Modelling, Identification and Control, ICMIC 2010, 483-488.
Yu, R., Breikin, T., & Wang, H. (2009). A HYBRID ANN-BASED FAULT DIAGNOSIS AND TOLERANCE METHOD AND ITS APPLICATION. IFAC Proceedings Volumes, 42 (8), 378-383. http://doi.org/10.3182/20090630-4-es-2003.00063
Dai, X., Gao, Z., Breikin, T., & Wang, H. (2009). Estimation delay compensation in high-gain observer-based parameter identification. Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference. http://doi.org/10.1109/cdc.2009.5400082
Abou-Zayed, U., Ashry, M., & Breikin, T. (2008). Experimental open-loop and closed-loop identification of a multi-mass electromechanical servo system. ICINCO 2008 - 5th International Conference on Informatics in Control, Automation and Robotics, Proceedings, SPSMC, 188-193.
Abou-Zayed, U., Ashry, M., & Breikin, T. (2008). Implementation of local optimal controller based on model identification of multi-mass electromechanical servo system. Proceedings of the IASTED International Conference on Modelling, Identification, and Control, MIC.
Dai, X., Gao, Z., Breikin, T., & Wang, H. (2008). Disturbance attenuation and fault detection via zero-pole assignment: A dynamic observer approach. IFAC Proceedings Volumes (IFAC-PapersOnline), 17 (1 PART 1). http://doi.org/10.3182/20080706-5-KR-1001.2600
Ashry, M., Abou-Zayed, U., & Breikin, T. (2008). Comparative robustness study of multivariable controllers for a gas turbine engine. Proceedings of the IASTED International Conference on Modelling, Identification, and Control, MIC.
Ashry, M., Abou-Zayed, U., & Breikin, T. (2008). Control of multivariable systems using modified local optimal controller. IFAC Proceedings Volumes (IFAC-PapersOnline), 17 (1 PART 1). http://doi.org/10.3182/20080706-5-KR-1001.2491
Gao, Z., Dai, X., Breikin, T., & Wang, H. (2008). High-gain observer-based parameter identification with application in a gas turbine engine. IFAC Proceedings Volumes (IFAC-PapersOnline), 17 (1 PART 1). http://doi.org/10.3182/20080706-5-KR-1001.2995
Xuewu Dai, , Breikin, T., Zhiwei Gao, , & Wang, H. (2008). Dynamic modelling and Robust Fault Detection of a gas turbine engine. 2008 American Control Conference. http://doi.org/10.1109/acc.2008.4586812
Ashry, M.M., Kamalova, Z.Z., & Breikin, T.V. (2008). Tuning of digital PID controller parameters using local optimal control. 2008 16th Mediterranean Conference on Control and Automation. http://doi.org/10.1109/med.2008.4602200
Dai, X., Kamalova, Z., Breikin, T., & Wang, H. (2007). Data guided reduced order modelling of a two shaft gas turbine engine. DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 14, 1299-1303.
Gao, Z., Breikin, T., & Wang, H. (2007). Discrete-time proportional-integral observer and observer-based controller for systems with unknown disturbances. 2007 European Control Conference (ECC). http://doi.org/10.23919/ecc.2007.7068385
Kamalova, Z., Breikin, T., Dai, X., & Wang, H. (2007). Design of genetic algorithm for on-line reduced-order dynamic modeling of gas turbines. 2007 European Control Conference (ECC). http://doi.org/10.23919/ecc.2007.7068418
Xuewu Dai, , Breikin, T., & Wang, H. (2006). An Algorithm for Identification of Reduced-Order Dynamic Models of Gas Turbines. First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06). http://doi.org/10.1109/icicic.2006.39
Gao, Z., Breikin, T., & Wang, H. (2006). Sensor fault estimator and its application for linear multi-variable dynamic systems with delayed state and input. 2006 IEEE International Conference on Robotics and Biomimetics. http://doi.org/10.1109/robio.2006.340203
Breikin, T., Lawton, A., & Bates, I. (2006). Application of evolutionary optimisation to space plasma turbulence modelling. Advances in Space Research, 38 (1), 7-15. http://doi.org/10.1016/j.asr.2005.02.104
Breikin, T.V., Kulikov, G.G., Arkov, V.Y., & Fleming, P.J. (2005). DYNAMIC MODELLING FOR CONDITION MONITORING OF GAS TURBINES: GENETIC ALGORITHMS APPROACH. IFAC Proceedings Volumes, 38 (1), 739-742. http://doi.org/10.3182/20050703-6-cz-1902.00124
Arkov, V., Kulikov, G., Fatikov, V., Kotenko, P., Breikin, T., & Epifanov, S. (2003). Intelligent control and monitoring unit and its investigation using Markov modelling. INTELLIGENT CONTROL SYSTEMS AND SIGNAL PROCESSING 2003, 431-435.
Lyantsev, O.D., Breikin, T.V., Kulikov, G.G., & Arkov, V.Y. (2003). Numerical algorithm for optimal multi-variable control of aero engines. 2003 European Control Conference (ECC). http://doi.org/10.23919/ecc.2003.7086513
Arkov, V., Kulikov, G., & Breikin, T. (2003). Optimal spectral resolution in system identification. Automatica, 39 (4), 661-668. http://doi.org/10.1016/s0005-1098(02)00277-7
Kim, S.K., Breikin, T.V., Hargrave, S.M., Thompson, H.A., Fleming, P.J., & Riley, S.J. (2002). STAGED COMBUSTION CONTROL FOR AVIATION ENGINES: A MULTI-OBJECTIVE OPTIMISATION APPROACH. IFAC Proceedings Volumes, 35 (1), 265-270. http://doi.org/10.3182/20020721-6-es-1901.01269
Arkov, V., Kulikov, G., & Breikin, T. (2002). LIFE CYCLE SUPPORT FOR DYNAMIC MODELLING OF GAS TURBINES. IFAC Proceedings Volumes, 35 (1), 55-60. http://doi.org/10.3182/20020721-6-es-1901.00915
Breikin, T.V., Hargrave, S.M., Thompson, H.A., Fleming, P.J., & Riley, S.J. (2002). Staged Combustion Control System Development for Aviation Gas Turbine Engines. Volume 2: Turbo Expo 2002, Parts A and B. http://doi.org/10.1115/gt2002-30040
Arkov, V.Y., Kulikov, G.G., & Breikin, T.V. (2002). Application of Markov Chains to Identification of Turbine Engine Dynamic Models. Volume 2: Turbo Expo 2002, Parts A and B. http://doi.org/10.1115/gt2002-30038
Arkov, V., Kulikov, G., Breikin, T., & Mort, N. (2000). Application of evolutionary optimization techniques in control systems identification. CONTROL APPLICATIONS OF OPTIMIZATION 2000, VOLS 1 AND 2, 29-34.
Kulikov, G., Arkov, V., & Breikin, T. (2000). Real-time modelling of gas turbines with optimal smoothing. CONTROL APPLICATIONS OF OPTIMIZATION 2000, VOLS 1 AND 2, 211-216.
Arkov, V., Kulikov, G., & Breikin, T. (2000). Optimal spectral resolution in systems identification. CONTROL APPLICATIONS OF OPTIMIZATION 2000, VOLS 1 AND 2, 23-28.
Breikin, T., Arkov, V., Kulikov, G., Kadirkamanathan, V., & Patel, V. (1998). On gas turbine engine and control system condition monitoring. (SAFEPROCESS'97): FAULT DETECTION, SUPERVISION AND SAFETY FOR TECHNICAL PROCESSES 1997, VOLS 1-3, 67-71.
Kulikov, G.G. (1998). Gas turbine engine fault detection using Markov simulation technique. International Conference on Simulation (1998). http://doi.org/10.1049/cp:19980617
Arkov, V.Y. (1998). Dynamic model identification of gas turbines. UKACC International Conference on Control (CONTROL '98). http://doi.org/10.1049/cp:19980429
Kulikov, G.G., Akhmetsafin, R.D., Fayzullin, A.N., & Breikin, T.V. (1998). Modified recurrent least squares algorithm for on-line closed-loop identification for processes with time delay. IEE Conference Publication, (455), 178-182.
Arkov, V., Breikin, T., & Kulikov, G. (1997). Fuzzy-Markov simulation technique for product testing equipment. INTELLIGENT MANUFACTURING SYSTEMS 1997 (IMS'97), 319-323.
Arkov, V.Y. (1997). Aircraft engine condition monitoring: stochastic identification and neural networks. Fifth International Conference on Artificial Neural Networks. http://doi.org/10.1049/cp:19970743
Arkov, V.Y., Kulikov, G.G., Breikin, T.V., & Patel, V.C. (1997). Chaotic and stochastic processes: Markov modeling approach. International Conference on Control of Oscillations and Chaos, Proceedings, 3, 488-491.
Kulikov, G.G. (1996). On Markov model applications in aircraft gas turbine engine full authority digital controller test-beds. UKACC International Conference on Control. Control '96. http://doi.org/10.1049/cp:19960537
Patel, V.C., Kadirkamanathan, V., Kulikov, G.G., Arkov, V.Y., & Breikin, T.V. (1996). Gas turbine engine condition monitoring using statistical and neural network methods. IEE Colloquium (Digest), (260).
Breikin, T., Kulikov, G., Arkov, V., & Fleming, P. On evolutionary optimisation of Markov models of aero engines. Proceedings of the 2000 IEEE International Symposium on Intelligent Control. Held jointly with the 8th IEEE Mediterranean Conference on Control and Automation (Cat. No.00CH37147). http://doi.org/10.1109/isic.2000.882930
Book chapters
Dai, X., Breikin, T., Wang, H., Kulikov, G., & Arkov, V. (2010). Modeling a Complex Aero-Engine Using Reduced Order Models. In Efficient Modeling and Control of Large-Scale Systems. (pp. 89-111). Springer US: http://doi.org/10.1007/978-1-4419-5757-3_4