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Comparable analysis of PID controller settings in order to ensure reliable operation of active foil bearings
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Polish Academy of Sciences, Institute of Fluid Flow Machinery, ul. Fiszera 14, 80-283 Gdansk, Poland
Gdansk University of Technology, Faculty of Mechanical Engineering and Ship Technology, Institute of Naval Architecture and Ocean Engineering, ul. Gabriela Narutowicza 11/12, 80-233 Gdansk, Poland
Gdańsk University of Technology, Digital Technologies Center, ul. Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland
Gdańsk University of Technology, Department of Intelligent Control and Decision Support Systems, Faculty of Electrical and Control Engineering, ul. Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland
Publication date: 2022-06-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2022;24(2):377-385
  • An optimization of controller parameter to prevent failures.
  • Prediction the behaviour of an active foil bearing controlled by PID controller.
  • The stochastic and hybrid algorithms were used for optimization.
  • This work could help prevent failures of active foil bearing.
In comparison to the traditional solutions, active bearings offer great operating flexibility, ensure better operating conditions over a wider range of rotational speeds and are safe to use. In order to ensure optimum bearing performance a bearing control system is used that adapts different geometries during device operation. The selection of optimal controller parameters requires the use of modern optimization methods that make it possible to quickly achieve the assumed parameters. This article presents the method that has been employed to select the parameters of a proportional integral derivative (PID) controller, in which both stochastic algorithms and hybrid methods have been compared. The results show that all of the used algorithms were able to reach the global optimum but only the hybrid algorithm was repeatable in all runs within a low value of the standard deviation. The best solution will be proposed in the future to control an active foil bearing. Analysing of this paper would help to prevent failures of active foil bearing used in the designed rotating machine.
Abdulameer A, Sulaiman M, Aras M S M, Saleem D. Tuning methods of PID controller for DC motor speed control. Indonesian Journal of Electrical Engineering and Computer Science 2016; 3(2): 343–349,
Ahmad I, Shahzad M, Palensky P. Optimal PID control of Magnetic Levitation System using Genetic Algorithm. 2014 IEEE International Energy Conference (ENERGYCON), 2014: 1429–1433,
Åström K J, Hägglund T. PID controllers: theory, design, and tuning. 2nd edition. Research Triangle Park, Instrument society of America: 1995: 354.
Åström K J, Panagopoulos H, Hägglund T. Design of PI controllers based on non-convex optimization. Automatica 1998; 34(5): 585–601,
Bahavarnia M, Tavazoei M S. A new view to Ziegler–Nichols step response tuning method: Analytic non-fragility justification. Journal of Process Control 2013; 23(1): 23–33,
Barbosa R S, Machado J A T, Ferreira I M. Tuning of PID controllers based on bode’s ideal transfer function. Nonlinear Dynamics 2004; 38(1–4): 305–321,
Blaut J, Breńkacz Ł. Application of the Teager-Kaiser energy operator in diagnostics of a hydrodynamic bearing. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22(4): 757–765,
Breńkacz Ł, Szewczuk-Krypa N, Witanowski Ł, Drosińska-Komor M. The basic control model of an active foil bearing. The Proceedings of the International Conference on Motion and Vibration Control 2020; 2020.15: 10033,
Breńkacz Ł, Witanowski Ł, Drosińska-Komor M, Szewczuk-Krypa N. Research and applications of active bearings: A state-of-the-art review. Mechanical Systems and Signal Processing 2021; 151: 107423,
Byrski W. Obserwacja i sterowanie w systemach dynamicznych. 1st edition. Uczelniane Wydaw. Naukowo-Dydaktyczne AGH: 2007: 314.
Castilla-Gutiérrez J, Fortes J C, Davila J M. Control and prediction protocol for bearing failure through spectral power density. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22(4): 651–657,
Chen H, Chang S. Genetic Algorithms Based Optimization Design of a PID Controller for an Active Magnetic Bearing. IJCSNS International Journal of Computer Science and Network Security 2006; 6(12): 95–99.
Chen K-Y Y, Tung P-C C, Tsai M-T T, Fan Y-H H. A self-tuning fuzzy PID-type controller design for unbalance compensation in an active magnetic bearing. Expert Systems with Applications 2009; 36(4): 8560–8570,
Chen X, Przystupa K, Ye Z et al. Forecasting short-term electric load using extreme learning machine with improved tree seed algorithm based on Lévy flight. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2022; 24(1): 153–162,
Chien I, Hrones J, Reswick J. On the automatic control of generalized passive systems. Trans. ASME 1952: 175–185.
Couzin I D, Laidre M E. Fission-fusion populations. Current Biology 2009; 19(15): 633–635,
Eberhart R, Kennedy J. New optimizer using particle swarm theory. Proceedings of the International Symposium on Micro Machine and Human Science 1995: 39–43,
Fan S-K S, Chang J-M. Dynamic multi-swarm particle swarm optimizer using parallel PC cluster systems for global optimization of largescale multimodal functions. Engineering Optimization 2010; 42(5): 431–451,
Fan S-K S, Jen C-H. An Enhanced Partial Search to Particle Swarm Optimization for Unconstrained Optimization. Mathematics 2019; 7(4): 357,
Fan S K S, Liang Y C, Zahara E. A genetic algorithm and a particle swarm optimizer hybridized with Nelder-Mead simplex search. Computers and Industrial Engineering 2006; 50(4): 401–425,
Fan S K S, Zahara E. A hybrid simplex search and particle swarm optimization for unconstrained optimization. European Journal of Operational Research 2007; 181(2): 527–548,
Ferfecki P, Zapoměl J. Reducing excessive vibration of rigid rotors mounted with hydrodynamic bearings by controlled excitation of the rotor supports. 2012.
Fung H W, Wang Q G, Lee T H. PI tuning in terms of gain and phase margins. Automatica 1998; 34(9): 1145–1149,
Ghasemi M, Davoudkhani I F, Akbari E et al. A novel and effective optimization algorithm for global optimization and its engineering applications: Turbulent Flow of Water-based Optimization (TFWO). Engineering Applications of Artificial Intelligence 2020; 92(February): 103666,
Goldberg D E. Genetic Algorithms in Search, Optimization and Machine Learning. 1st edition. Addison-Wesley Longman Publishing Co., Inc.: 1989.
Hybrid Grey Wolf and Cuckoo Search Optimization Algorithm. [].
Heppner F H, Grenander U. A Stochastic Non-Linear Model for Bird Flocking. The Ubiquity of Chaos 1990; (January 1990): 233–238.
Hernández-Alvarado R, García-Valdovinos L G, Salgado-Jiménez T et al. Neural network-based self-tuning PID control for underwater vehicles. Sensors (Switzerland) 2016; 16(9): 1–18,
Jaiswal S, Suresh Kumar C, Seepana M M, Babu G U B. Design of Fractional Order PID Controller Using Genetic Algorithm Optimization Technique for Nonlinear System. Chemical Product and Process Modeling 2020: 1–11,
Khishe M, Mosavi M R. Chimp optimization algorithm. Expert Systems with Applications 2020; 149: 113338,
Kicinski J. Rotor Dynamics. 1st edition. IFFM Publisher: 2006.
Korsane D T, Yadav V, Raut K H. PID Tuning Rules for First Order plus Time Delay System. International Journal Of Innovative Research In Electrical, Electronics, Instrumentation And Control Engineering 2014; 2(1): 582–586.
Lampart P, Yershov S, Rusanov A. Increasing flow efficiency of high-pressure and low-pressure steam turbine stages from numerical optimization of 3D blading. Engineering Optimization 2005; 37(2): 145–166,
Maior C B S, das Chagas Moura M, Lins I D. Particle swarm-optimized support vector machines and pre-processing techniques for remaining useful life estimation of bearings. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2019; 21(4): 610–619,
Manoj K, Ashish P. PID Controller Tuning using Ziegler-Nichols Method for Speed Control of DC Motor. 2014; 03(13): 2924–2929.
Mendes J, Osório L, Araújo R. Self-tuning PID controllers in pursuit of plug and play capacity. Control Engineering Practice 2017; 69(June): 73–84,
Michalewicz Z. Genetic algorithms + data structures = evolutionary programmes. Warszawa, WNT: 1996.
Mirjalili S, Lewis A. The Whale Optimization Algorithm. Advances in Engineering Software 2016; 95: 51–67,
Mirjalili S, Lewis A, Sadiq A S. Autonomous Particles Groups for Particle Swarm Optimization. Arabian Journal for Science and Engineering 2014; 39(6): 4683–4697,
Morosi S, Santos I F. Experimental Investigations of Active Air Bearings. Volume 7: Structures and Dynamics, Parts A and B, ASME: 2012; (April): 1–10,
Nalepa K, Pietkiewicz P, Żywica G. Development of the foil bearing technology. Technical Sciences 2009; 12(1): 229–240,
Olszewski A, Żochowski T, Gołębiewski G. Analysis of the load-carrying capacity of a hydrodynamic water-lubricated bearing in a hydroelectric power plant. Tribologia 2018; 278(2): 103–110,
Peng J-P, Carpino M. Finite Element Approach to the Prediction of Foil Bearing Rotor Dynamic Coefficients. Journal of Tribology 1997; 119(1): 85–90,
Pessen D W. A New Look at PID-Controller Tuning. Journal of Dynamic Systems, Measurement, and Control 1994; 116(September 1994): 553–557,
Priyambodo T K, Putra A E, Dharmawan A. Optimizing Control based on Ant Colony Logic for Quadrotor Stabilization. 2015. doi:10.1109/ICARES.2015.7429820,
Psonis T K, Nikolakopoulos P G, Mitronikas E. Design of a PID Controller for a Linearized Magnetic Bearing. International Journal of Rotating Machinery 2015.
Puchalski B, Duzinkiewicz K, Rutkowski T. Multi-region fuzzy logic controller with local PID controllers for U-tube steam generator in nuclear power plant. Archives of Control Sciences 2015; 25(4): 429–444,
Puchalski B, Rutkowski T A, Duzinkiewicz K. Fuzzy Multi-Regional Fractional PID controller for Pressurized Water nuclear Reactor. ISA Transactions 2020; 103: 86–102,
Puchalski B, Rutkowski T, Tarnawski J, Duzinkiewicz K. Comparison of tuning procedures based on evolutionary algorithm for multi-region fuzzy-logi PID controller for non-linear plant. 2015 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015 2015: 897–902,
Regad M, Helaimi M, Taleb R et al. Fractional Order PID Control of Hybrid Power System with Renewable Generation Using Genetic Algorithm. Proceedings of 2019 the 7th International Conference on Smart Energy Grid Engineering, SEGE 2019 2019: 139–144,
Singh S S K, Abdullah S, Mohamed N A N. Reliability analysis and prediction for time to failure distribution of an automobile crankshaft. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2015; 17(3): 408–415,
Siva Srinivas R, Tiwari R, Kannababu C. Application of active magnetic bearings in flexible rotordynamic systems – A state-of-the-art review. Mechanical Systems and Signal Processing 2018; 106: 537–572,
Smolinski M, Perkowski T, Mystkowski A et al. AMB flywheel integration with photovoltaic system for household purpose – modelling and analysis. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2016; 19(1): 86–94,
Tandon B. Genetic Algorithm Based Parameter Tuning of Pid Controller for Composition Control System. International Journal of Engineering Science and Technology 2011; 3(8): 6705–6711.
Yang X-S. Recent Advances in Swarm Intelligence and Evolutionary Computation. Studies in. Springer: 2015. doi:10.1007/978-3-319-13826-8,
Zdziebko P, Martowicz A. Study on the temperature and strain fields in gas foil bearings – measurement method and numerical simulations. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2021; 23(3): 540–547,
Żywica G, Kaczmarczyk T Z. Experimental evaluation of the dynamic properties of an energy microturbine with defects in the rotating system. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2019; 21(4): 670–678,
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