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MIMO intelligent-PID controller design for half car system based on model free control technique

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A novel decoupled Multi-Input-Multi-Output Model Free Control strategy is presented in this paper to improve the performance of an active suspension system implemented on a half car model. To damp vibrations generated by road excitation, an algebraic online compensator was integrated in the structure of a classical PID controller to avoid the impact of unpredictable disturbances. The key element of the proposed technique is a non-asymptotic observer that can avoid the use of statistical conventional techniques. Furthermore, the advantage of easy implementation is achieved where only two accelerometers are sufficient and adequate. A comparison with classical PID and LQR is provided to demonstrate the improvement made by the proposed scheme.
Rocznik
Strony
953--969
Opis fizyczny
Bibliogr. 25 poz., rys., tab.
Twórcy
autor
  • Laboratory of Mechanics, Modelling and Production (LA2MP), National School of Engineering of Sfax, University of Sfax, Tunisia
  • Laboratory of Mechanics, Modelling and Production (LA2MP), National School of Engineering of Sfax, University of Sfax, Tunisia
  • Hacettepe University Beytepe, Department of Mechanical Engineering, Ankara, Turkey
autor
  • Laboratory of Mechanics, Modelling and Production (LA2MP), National School of Engineering of Sfax, University of Sfax, Tunisia
  • Laboratory of Mechanics, Modelling and Production (LA2MP), National School of Engineering of Sfax, University of Sfax, Tunisia
  • Laboratory of Mechanics, Modelling and Production (LA2MP), National School of Engineering of Sfax, University of Sfax, Tunisia
Bibliografia
  • 1. Demir O., Keskin I., Cetin S., 2012,Modeling and control of a nonlinear half-vehicle suspension system: a hybrid fuzzy logic approach, Nonlinear Dynamics, 67, 3, 2139-2151.
  • 2. Ekoru J.E., Pedro J.O., 2013, Proportional-integral-derivative control of nonlinear half-car electro-hydraulic suspension systems, Journal of Zhejiang University Science A, 14, 6, 401-416.
  • 3. Faris W.F., Ihsan S.I., Ahmadian M., 2009, Transient and steady state dynamic analysis of passive and semi-active suspension systems using half-car model, International Journal of Modelling, Identification and Control, 6, 1, 62-71.
  • 4. Ferdek U., Łuczko J., 2015, Performance comparison of active and semi-active SMC and LQR regulators in a quarter-car model, Journal of Theoretical and Applied Mechanics, 53, 4, 811-822.
  • 5. Fliess M., Join C., 2013, Model-free control, International Journal of Control, 86, 2228-2252.
  • 6. Haddar M., Baslamisli S.C., Chaari R., Chaari F., Haddar M., 2019a, Road profile identification with an algebraic estimator, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 233, 4, 1139-1155.
  • 7. Haddar M., Baslamisli S.C., Chaari F., Haddar M., 2017, On-line adaptive scaling parameter in active disturbance rejection controller, [In:] Felkaoui A., Chaari F., Haddar M. [Ed.] Rotating Machinery and Signal Processing, Springer, pp. 79-86
  • 8. Haddar M., Chaari R., Baslamisli S.C., Chaari F., Haddar M., 2019b, Intelligent PD controller design for active suspension system based on robust model-free control strategy, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, DOI: 10.1177/0954406219836443.
  • 9. Hasbullah F., Faris W.F.,Darsivan F.J., 2015, Ride comfort performance of a vehicle using active suspension system with active disturbance rejection control, International Journal of Vehicle Noise and Vibration, 11, 78-101.
  • 10. Hasbullah F., Faris W. F., 2017, Simulation of disturbance rejection control of half-car active suspension system using active disturbance rejection control with decoupling transformation, Journal of Physics, Conference Series, 949, 1, 012025.
  • 11. Hua C., Chen J., Li Y., Li L., 2018, Adaptive prescribed performance control of half-car active suspension system with unknown dead-zone input, Mechanical Systems and Signal Processing, 111, 135-148.
  • 12. ISO 2631-1:1997, Evaluation of human exposure to whole-body vibration – Part 1: General requirements.
  • 13. ISO 8608: Mechanical Vibration-Road Surface Profiles-Reporting of Measured Data, International Standardization Organization, Geneva, Switzerland, 199.
  • 14. León-Vargas F., Garelli F., Zapateiro M., 2018, Limiting vertical acceleration for ride comfort in active suspension systems, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 232, 3, 223-232.
  • 15. Łuczko J., Ferdek U., 2016, Continuous and discrete sliding mode control of an active car suspension system, Journal of Theoretical and Applied Mechanics, 54, 3-11.
  • 16. Maciejewski I., Krzyżyński T., Pecolt S., Chamera S., 2019, Semi-active vibration control of horizontal seat suspension by using magneto-rheological damper, Journal of Theoretical and Applied Mechanics, 57, 2, 411-420.
  • 17. Pan H., Sun W., Gao H., Hayat T., Alsaadi F., 2015, Nonlinear tracking control based on extended state observer for vehicle active suspensions with performance constraints, Mechatronics, 30, 363-370.
  • 18. Phu D. X., Huy T.D, Mien V., Choi S.B., 2018, A new composite adaptive controller featuring the neural network and prescribed sliding surface with application to vibration control, Mechanical Systems and Signal Processing, 107, 409-428.
  • 19. Pusadkar U.S., Chaudhari S.D., Shendge P.D., Phadke S.B., 2019, Linear disturbance observer based sliding mode control for active suspension systems with non-ideal actuator, Journal of Sound and Vibration, 442, 428-444.
  • 20. Rajamani R., 2011, Vehicle Dynamics and Control, Springer Science & Business Media.
  • 21. Rath J.J., Veluvolu K.C., Defoort M., 2015, Simultaneous estimation of road profile and tire road friction for automotive vehicle, IEEE Transactions on Vehicular Technology, 64, 10, 4461-4471.
  • 22. Senthil Kumar P., Sivakumar K., Kanagarajan R., Kuberan S., 2018, Adaptive Neuro Fuzzy Inference System control of active suspension system with actuator dynamics, Journal of Vibroengineering, 20, 1, 541-549.
  • 23. Wakeham K.J., Rideout D.G., 2011, Model complexity requirements in design of half car active suspension controllers, [In:] ASME 2011 Dynamic Systems and Control Conference and Bath/ASME Symposium on Fluid Power and Motion Control, Virginia.
  • 24. Wang H.P., Mustafa G.I., Tian Y., 2018, Model-free fractional-order sliding mode control for an active vehicle suspension system, Advances in Engineering Software, 115, 452-461.
  • 25. Wang J., Jin F., Zhou L., Li P., 2019, Implementation of model-free motion control for active suspension systems, Mechanical Systems and Signal Processing, 119, 589-602.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f563e9fb-4a87-4cb9-8321-7adde61e687f
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