PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

TP transformation based ocntroller and observer design of the inverted pendulum

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
PL
Transformatorowy sterownik TP i konstrukcja obserwatora odwróconego wahadła
Języki publikacji
EN
Abstrakty
EN
The paper discusses that applying of CNO and IRNO type weighting functions results different TP models, including controller and observer. Selection of weighting functions has influence on the TP model transformation and the LMI based design. Present paper introduces the LMI based observer and controller design of the inverted pendulum via the TP model transformation based method using CNO and IRNO type weighting functions. The TP transformation is accomplished by qLPV modeling and HOSVD method. The paper gives a conclusion and a comparison of the original and estimated state variables and the impact of applying two types of weighting functions. The aim of present paper is to prove that using different type of weighting functions influences the TP models and LMI methods, but LMIs still result feasible solution for controller and observer design. Furthermore the modification allows to choose the better controller/observer.
PL
W artykule wykazano, ze zastosowanie funkcji wagowych typu CNO i IRNO skutkuje różnymi modelami TP, w tym kontrolerem i ˙ obserwatorem. Wybór funkcji wagowej ma wpływ na transformację modelu TP i konstrukcję w oparciu o LMI. W niniejszym artykule przedstawiono projekt obserwatora i kontrolera w oparciu o LMI odwróconego wahadła za pomocą metody opartej na transformacji modelu TP z wykorzystaniem funkcji wagowych typu CNO i IRNO. Transformacja TP realizowana jest za pomocą modelowania qLPV i metody HOSVD. Artykuł zawiera wnioski i porównanie pierwotnych i oszacowanych zmiennych stanu oraz wpływu zastosowania dwóch typów funkcji wag. Celem niniejszego artykułu jest wykazanie, ze zastosowanie różnego rodzaju funkcji wagowych wpływa na modele TP i metody LMI, ale LMI nadal dają wykonalne rozwiązanie dla konstrukcji kontrolera i obserwatora. Ponadto modyfikacja pozwala wybrac lepszego kontrolera/obserwatora.
Rocznik
Strony
34--39
Opis fizyczny
Bibliogr. 31., rys.
Twórcy
  • Széchenyi István University, Measurement and Information Systems, Department of Automation, Gyor, Hungary H-902
  • Széchenyi István University, Measurement and Information Systems, Department of Automation, Gyor, Hungary H-902
Bibliografia
  • [1] Baranyi P.: TP model transformation as a way to LMI-basedcontroller design IEEE Transactions on Industrial Electronics,51(2), pp. 387–400, 2004.
  • [2] Baranyi P.: How to Vary the Input Space of a TS Fuzzy Model:a TP Model Transformation Based Approach, IEEE Transacations on Fuzzy Systems, 30(2), pp. 345–356, 2021.
  • [3] Baranyi P.: Extracting LPV and qLPV Structures from State-Space Functions: A TP Model Transformation Based Framework, IEEE Transactions on Fuzzy Systems, 28(3), pp. 499–509, 2017.
  • [4] Nagy Sz., Petres Z., Baranyi P.: TP tool - A MATLAB toolbox for TP model transformation 8th International Symposiumof Hungarian Researchers on Computational Intelligence andInformatics, CINTI, pp. 483–495, 2007.
  • [5] Wéber A., Kuczmann M.: TP Transformation of the InvertedPendulum, 2020 2nd IEEE International Conference on Gridding and Polytope Based Modelling and Control (GPMC),pp. 13–18, 2020.
  • [6] Wéber A., Kuczmann M.: Study of the TP transformation viathe Inverted Pendulum Example, Acta Technica Jaurinensis,14(1), pp. 1–23, 2021.
  • [7] Yam Y., Baranyi P., Yamg C.T.: Reduction of Fuzzy RuleBase via Singular Value Decomposition, IEEE Transactionson Fuzzy Systems, 7(2), pp. 120–132, 1999.
  • [8] Bergqvist G., Larsson E.: The Higher Order Singular ValueDecomposition: Theory and an Application, IEEE Signal Processing Magazine, 27(3), pp. 151–154, 2010.
  • [9] Baranyi P., Szeidl P., Várlaki P., Yam Y.: Definition of theHOSVD Based Canonical Form of Polytopic Dynamic Models, Proceedings of the 2006 IEEE International Conferenceon Mechatronics, pp. 660–665, 2006.
  • [10] Szeidl P., Várlaki P.: HOSVD Based Canonical Form for Polytopic Models of Dynamic Systems, Journal of Advanced Computational Intelligence and Intelligent Informatics, 13(1), pp.52–60, 2009.
  • [11] Baranyi P., Yam Y., Várlaki P.: Tensor Product Model Transformation in Polytopic Model Based Control, 1st Edition, CRCPress, Taylor and Francis Group, 2018.
  • [12] Baranyi P.: The generalized TP model transformation for TSfuzzy model manipulation and generalized stability verification,IEEE Transactions on Fuzzy Systems, 22(4), pp. 934–948,2014.
  • [13] Wang T., Bi Y., Hou T., Liu B., Cui J.: An Efficient TP ModelTransformation Algorithm for Robust Visual Servoing in thePresence of Uncertain Data, Acta Polytechnica Hungarica,17(6), 2020.
  • [14] Boonyaprapasorn A., Kuntanapreeda S., Sangpet T.,Ngiamsunthorn S., Pengwang E.: Biological Pest ControlBased on Tensor Product Transformation Method, Acta Polytechnica Hungarica, 17(6), 2020.
  • [15] Petres Z., Reskó B., Baranyi P.: TP Model TransformationBased Control of the TORA System, Production Systems andInformation Engineering, pp. 159–175, 2004.
  • [16] Korondi P.: Tensor Product Model Transformation-based Sliding Surface Design, Acta Polytechnica Hungarica, 3(4), pp.23–35, 2006.
  • [17] Kolonic F., Poljugan A., Petrovic I.: Tensor Product ModelTransformation-based Controller Design for Gantry CraneControl System-an Application Approach, Acta PolytechnicaHungarica, 3(4), pp. 95–112, 2006.
  • [18] Szollosi, A.,Baranyi, P.: Influence of the tensor product modelrepresentation of qLPV models on the feasibility of linear matrix inequality, Asian Journal of Control, 18(5), pp. 1–15, 2016.
  • [19] Szollosi, A.,Baranyi, P.: Influence of the tensor product modelrepresentation of qLPV models on the feasibility of linear matrix based stability analysis, Asian Journal of Control, 20(3),pp. 1–17, 2018.
  • [20] Wang H., Dong H., He L., Shi Y., Zhang Y.: Design and Simulation of LQR Controller with the Linear Inverted Pendulum,2010 International Conference on Electrical and Control Engineering, Jun. 2010.
  • [21] Prasad L.B., Tyagi B., Gupta H.O.: Optimal control of nonlinear inverted pendulum dynamical system with disturbanceinput using PID controller LQR, 2011 IEEE International Conference on Control System, Computing and Engineering, Nov.2011.
  • [22] Kuczmann M.: Comprehensive Survey of PID Controller Design for the Inverted Pendulum, Acta Technica Jaurinensis,2(1), pp. 55–81, 2019.
  • [23] Kuczmann M.: State Space Based Linear Controller Designfor the Inverted Pendulum, Acta Technica Jaurinensis, 12(2),pp. 130–147, 2019.
  • [24] Grof P., Yam Y.: Furuta Pendulum - a Tensor Product Modelbased Design Approach Case Study, IEEE International Conference on Systems, Man, and Cybernetics, pp. 2620–2625,2015.
  • [25] Nagy Sz., Petres Z., Baranyi P., Szeidl L., MichelbergerP.: Polytopic Decomposition of the Linear Parameter-varyingModel of the Parallel-type Double inverted Pendulum, 200711th International Conference on Intelligent Engineering Systems, pp. 271-275.
  • [26] Iles S., Matusko J., Kolonic F.: TP transformation based control of rotary pendulum, IEEE 2011 Proceedings of the 34thInternational Convention MIPRO, May 2011.
  • [27] Nagy Sz., Petres Z., Baranyi P.: TP Model Transformation Based Controller Design for the Parallel-type Double Inverted Pendulum, June 2008 IEEE International Conferenceon Fuzzy Systems.
  • [28] Siradjuddin I., Amalia Z., Setiawan B., Wicaksono R.P., Yudaningtyas E.: Stabilising a Cart Inverted Pendulum SystemUsing Pole Placement Control Method, 2017 15th International Conference on Quality in Research (QiR) : InternationalSymposium on Electrical and Computer Engineering, 2017.
  • [29] Guang-Ren D., Hai-Hua Y.: LMIs in Control Systems: Analysis, Design and Applications, 1st Edition, CRC Press, Taylorand Francis Group, 2013.
  • [30] Tanaka K., Wang H.O.: Fuzzy Control Systems Design andAnalysis: A linear Matrix Inequality Approach John Wiley andSons, 2001.
  • [31] Tanaka K., SANO M.: On the Concepts of Regulator and Observer of Fuzzy Control, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference, Jun. 1994.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b448de6b-d78e-4efc-b671-17ebd49bf755
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.