Highly nonlinear systems estimation using extended and unscented kalman filters

• Autorzy: Laamari Yahia , Allaoui Samia , Chafaa Kheireddine , Bendaikha Abdelmalik

Identyfikatory

DOI

10.15199/48.2021.05.20

Warianty tytułu

PL

Nieliniowe oszacowanie systemów przy użyciu filtrów Kalmana

• Języki publikacji: EN

Abstrakty

EN

The main idea of this study is to evaluate the estimation performance of extended and unscented Kalman filters (EKF and UKF). So, these latter are introduced to estimate the dynamic states of a similar model operating with identical covariance matrices in the same situation. The mean square error (MSE) criterion is used to quantify the estimation error between the actual and the estimated values. The simulation results obtained with Matlab/ Simulink software confirm the superiority and efficiency of UKF over EKF, especially when the system is highly non-linear under process and measurement noises, such is the case of the inverted double pendulum mounted on a cart (DIPC).

PL

Główną ideą tego badania jest ocena wydajności estymacji rozszerzonych filtrów Kalmana (EKF i UKF). Te ostatnie zostały wprowadzone w celu oszacowania stanów dynamicznych podobnego modelu działającego z identycznymi macierzami kowariancji. Kryterium błędu średniokwadratowego (MSE) służy do ilościowego określenia błędu oszacowania między wartościami rzeczywistymi i szacunkowymi. Wyniki symulacji uzyskane za pomocą oprogramowania Matlab i Simulink potwierdzają wyższość i wydajność UKF nad EKF, zwłaszcza gdy system jest wysoce nieliniowy

Słowa kluczowe

EN

nonlinear system; double inverted pendulum; Kalman filter; state estimation

PL

filtr Kalmana; system nieliniowy; dynamika

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2021
• Tom: R. 97, nr 5
• Strony: 111--115
• Opis fizyczny: Bibliogr. 17 poz., rys.

Twórcy

autor

Laamari Yahia

• Electrical Engineering Department, Mohamed Boudiaf University of M’Sila, 28000, Algeria

autor

Allaoui Samia

• Electronics Department, Faculty of Technology, Batna 2 University, Fesdis, Batna 05078, Algeria

autor

Chafaa Kheireddine

• Electronics Department, Faculty of Technology, Batna 2 University, Fesdis, Batna 05078, Algeria

autor

Bendaikha Abdelmalik

• Electrical Engineering Department, Mohamed Boudiaf University of M’Sila, 28000, Algeria

Bibliografia

• [1] Zheng M., Ikeda K., Shimomura T., Parameter Estimation of Rotary Inverted Pendulum based on Unscented Kalman Filter, SICE-ICASE International Joint Conference 2006, Bexco, Busan, Korea, Oct. 18-21,(2006).
• [2] Zhao J. , Mili L., A Theoretical Framework of Robust H-Infinity Unscented Kalman Filter and Its Application to Power System Dynamic State Estimation, IEEE Transactions on Signal Processing, 67 (2019),n.10 , 2734 – 2746.
• [3] Julier S., Uhlmann, J., Unscented Filtering and Nonlinear Estimation, Proceeding of the IEEE, 92 (2004),n. 3, 401- 422.
• [4] Julier, S. , Uhlmann J., Durrant Whyte H.F., A New Method for the Nonlinear Transformation of Means and Covariances in Filters and Estimators, IEEE Trans. Automat. Control, 45(2000), 477-482.
• [5] Kalman R. E., A new approach to linear filtering and prediction problems,” J. Basic Eng., 82(1960), n.1, 35–45.
• [6] Qu X., Xie L., Recursive source localization by time difference of arrival sensor networks with sensor position uncertainty, IET Control Theory and Applications, 8 (2014),n.18, 2305–2315.
• [7] Wang Y., Qiu Z., Qu X., An Improved Unscented Kalman Filter for Discrete Nonlinear Systems with Random Parameters, Discrete Dynamics in Nature and Society, 2017, Article ID 7905690, 10 pages.
• [8] Yin Z., Gao F., Zhang Y., Du C. Li G., and Sun X., A review of nonlinear Kalman filter appling to sensorless control for AC motor drives, in CES Transactions on Electrical Machines and Systems, 3(2019), n. 4, 351-362.
• [9] Jafarzadeh, S., Lascu, C., Fadali, M. S., State Estimation of Induction Motor Drives Using the Unscented Kalman Filter, IEEE Transactions on Industrial Electronics, 59 (2012), n. 11.
• [10] Jha R., Senroy N., Warms based dynamic states and parameters estimation using least squares estimation and unscented Kalman filter, IEEE Innovative Smart Grid Technologies- Assia (ISGT-Assia), 2017.
• [11] W. Ende, H. Shenghua, Robust control of the three-phase voltage-source PWM rectifier using EKF load current observer, Przegląd ElektrotechnicznY (Electrical Review), ISSN 0033- 2097, R. 89 NR 3a/2013, 189-193.
• [12] Bourahla M., Ghaouti L., Bouchetata N., Sensorless field oriented control of PMSM based on the extended KALMAN filter observer, Przegląd Elektrotechniczny, 92 (2016), nr 12, 249-254
• [13] Hashemi Z., Rahideh A., Rotor Electrical Fault Detection of Wind Turbine Induction Generators Using an Unscented Kalman Filter, Iran J Sci Technol Trans Electr Eng 44(2020), 979–988.
• [14]Laamari Y., Chafaa K., Athamena B., Particle swarm optimization of an extended Kalman filter for speed and rotor flux estimation of an induction motor drive, Electrical Engineering 97(2015),n.2,129–138
• [15] Zheng B., , Fu P., Li B., Yuan X., A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance, Sensors 18(2018), 808.
• [16] Dhanni, Y. K., single input variable universe fuzzy controller with contraction-expansion factor for inverted pendulum in real time, Advances in Electrical and Electronic Engineering. 10(2012),n. 5.
• [17] Yi J., Yubazaki N., Hirotac K., Stabilization control of seriestype double inverted pendulum systems using the SIRMs dynamically connected fuzzy inference model, Artificial Intelligence in Engineering, 15(2001), n.3, 297-308.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).