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Journal articles on the topic 'Adaptive obsever'

Author: Grafiati

Published: 8 February 2025

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1

Souaihia, Maamar, Bachir Belmadani, and Rachid Taleb. "A robust state of charge estimation for multiple models of lead acid battery using adaptive extended Kalman filter." Bulletin of Electrical Engineering and Informatics 9, no. 1 (February 1, 2020): 1–11. http://dx.doi.org/10.11591/eei.v9i1.1486.

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An accurate estimation technique of the state of charge (SOC) of batteries is an essential task of the battery management system. The adaptive Kalman filter (AEKF) has been used as an obsever to investigate the SOC estimation effectiveness. Therefore, The SOC is a reflexion of the chemistry of the cell which it is the key parameter for the battery management system. It is very complex to monitor the SOC and control the internal states of the cell. Three battery models are proposed and their state space models have been established, their parameters were identified by applying the least square method. However, the SOC estimation accuracy of the battery depends on the model and the efficiency of the algorithm. In this paper, AEKF technique is presented to estimate the SOC of Lead acid battery. The experimental data is used to identify the parameters of the three models and used to build different open circuit voltage–state of charge (OCV-SOC) functions relationship. The results shows that the SOC estimation based-model which has been built by hight order RC model can effectively limit the error, hence guaranty the accuracy and robustness.

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2

Kim, Hyeon-Sik, Seung-Ki Sul, Hyunjae Yoo, and Jaeyoon Oh. "Distortion-Minimizing Flux Observer for IPMSM Based on Frequency-Adaptive Observers." IEEE Transactions on Power Electronics 35, no. 2 (February 2020): 2077–87. http://dx.doi.org/10.1109/tpel.2019.2920691.

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3

Porter, La Moyne L., and Kevin M. Passino. "Genetic adaptive observers." Engineering Applications of Artificial Intelligence 8, no. 3 (June 1995): 261–69. http://dx.doi.org/10.1016/0952-1976(95)00007-n.

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4

Benzemrane, Khadidja, Gilney Damm, and Giovanni L. Santosuosso. "Adaptive Observer and Kalman Filtering." IFAC Proceedings Volumes 41, no. 2 (2008): 3865–70. http://dx.doi.org/10.3182/20080706-5-kr-1001.00650.

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5

HAO, Shuanghui, and Teruo TUSJI. "Adaptive Nonlinear Control Using Observer." Transactions of the Society of Instrument and Control Engineers 34, no. 4 (1998): 318–25. http://dx.doi.org/10.9746/sicetr1965.34.318.

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6

Yang, Jong-Kun, Chang-Ho Hyun, Jae-Hun Kim, Euntai Kim, and Mignon Park. "Indirect Adaptive Fuzzy Observer Design." Journal of Korean Institute of Intelligent Systems 14, no. 7 (December 1, 2004): 927–33. http://dx.doi.org/10.5391/jkiis.2004.14.7.927.

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7

Eaton, Ray. "REDUCED ORDER ADAPTIVE OBSERVER BACKSTEPPING." IFAC Proceedings Volumes 35, no. 1 (2002): 1–6. http://dx.doi.org/10.3182/20020721-6-es-1901.00081.

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8

Paesa, D., A. Baños, and C. Sagues. "Optimal reset adaptive observer design." Systems & Control Letters 60, no. 10 (October 2011): 877–83. http://dx.doi.org/10.1016/j.sysconle.2011.07.007.

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9

Wei, Yi-Heng, Zhen-Yuan Sun, Yang-Sheng Hu, and Yong Wang. "On fractional order adaptive observer." International Journal of Automation and Computing 12, no. 6 (November 6, 2015): 664–70. http://dx.doi.org/10.1007/s11633-015-0929-3.

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10

Marino, Riccardo, and Patrizio Tomei. "Adaptive notch filters are local adaptive observers." International Journal of Adaptive Control and Signal Processing 30, no. 1 (June 1, 2015): 128–46. http://dx.doi.org/10.1002/acs.2582.

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11

Hoang, T. D., and A. A. Pyrkin. "Adaptive position observer for moving object." Journal of Physics: Conference Series 1864, no. 1 (May 1, 2021): 012027. http://dx.doi.org/10.1088/1742-6596/1864/1/012027.

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12

LI, Yong, Yoh YONEZAWA, and Yukio NISHIMURA. "A Design of Robust Adaptive Observer." Transactions of the Society of Instrument and Control Engineers 25, no. 6 (1989): 717–19. http://dx.doi.org/10.9746/sicetr1965.25.717.

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13

WAKITA, Eiji. "Consolidation Settlement Prediction by Adaptive Observer." Doboku Gakkai Ronbunshu, no. 481 (1993): 49–58. http://dx.doi.org/10.2208/jscej.1993.481_49.

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14

Hulhoven, X., and Ph Bogaerts. "MAXIMUM LIKELIHOOD ADAPTIVE OBSERVER FOR BIOPROCESSES." IFAC Proceedings Volumes 38, no. 1 (2005): 85–90. http://dx.doi.org/10.3182/20050703-6-cz-1902.02218.

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15

Dong, Zhe, Bowen Li, Miao Liu, Di Jiang, and Xiaojin Huang. "ADAPTIVE STATE-OBSERVER FOR NUCLEAR REACTORS." Proceedings of the International Conference on Nuclear Engineering (ICONE) 2019.27 (2019): 1934. http://dx.doi.org/10.1299/jsmeicone.2019.27.1934.

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16

Sariyildiz, Emre, and Kouhei Ohnishi. "An Adaptive Reaction Force Observer Design." IEEE/ASME Transactions on Mechatronics 20, no. 2 (April 2015): 750–60. http://dx.doi.org/10.1109/tmech.2014.2321014.

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17

FRADKOV, ALEXANDER, HENK NIJMEIJER, and ALEXEY MARKOV. "ADAPTIVE OBSERVER-BASED SYNCHRONIZATION FOR COMMUNICATION." International Journal of Bifurcation and Chaos 10, no. 12 (December 2000): 2807–13. http://dx.doi.org/10.1142/s0218127400001869.

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The problem of synchronizing two nonlinear systems (transmitter and receiver) is considered. A simple design of an adaptive observer for estimating the unknown parameters of the transmitter is proposed based on the design of quadratic Lyapunov function for the error system. The results are illustrated by an example of signal transmission based on a pair of synchronizing Chua circuits.

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18

Ahmed-Ali, T., and F. Lamnabhi-Lagarrigue. "Sliding Observer and Adaptive Controller Design." IFAC Proceedings Volumes 31, no. 18 (July 1998): 335–38. http://dx.doi.org/10.1016/s1474-6670(17)42014-3.

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19

Guo, L., A. Schöne, and X. Ding. "Observer-based Nonlinear Adaptive Tracking Control." IFAC Proceedings Volumes 26, no. 2 (July 1993): 175–78. http://dx.doi.org/10.1016/s1474-6670(17)49102-6.

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20

Besançon, Gildas. "Remarks on nonlinear adaptive observer design." Systems & Control Letters 41, no. 4 (November 2000): 271–80. http://dx.doi.org/10.1016/s0167-6911(00)00065-7.

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21

Riedel, Thomas. "An Observer for Adaptive Intersection Control." IFAC Proceedings Volumes 30, no. 8 (June 1997): 859–64. http://dx.doi.org/10.1016/s1474-6670(17)43929-2.

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22

Pérez-Estrada, A. J., G. L. Osorio-Gordillo, M. Darouach, and M. Alma. "Adaptive observer design for LPV systems." IFAC-PapersOnLine 52, no. 28 (2019): 140–45. http://dx.doi.org/10.1016/j.ifacol.2019.12.361.

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23

Uetake, Y. "Adaptive observer for continuous descriptor systems." IEEE Transactions on Automatic Control 39, no. 10 (1994): 2095–100. http://dx.doi.org/10.1109/9.328803.

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24

ZHU, FANG-LAI, and MAO-YIN CHEN. "OBSERVER-BASED SYNCHRONIZATION OF UNCERTAIN CHAOTIC SYSTEMS: COMPARISON BETWEEN REDUCED-ORDER AND FULL-ORDER OBSERVERS." International Journal of Bifurcation and Chaos 18, no. 10 (October 2008): 3129–36. http://dx.doi.org/10.1142/s0218127408022299.

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Within the drive-response configuration, this paper considers the synchronization of uncertain chaotic systems based on observers. Even if there are unknown disturbances and parameters in the drive system, a robust adaptive full-order observer can be used to realize chaos synchronization. Further, we develop a reduced-order observer-based response system to synchronize the drive system. By choosing a special reduced-order gain matrix, the reduced-order observer-based response system turns out to be linear and can eliminate the influence of the unknown disturbances and parameters directly. We also discuss the above mentioned two kinds of observers in numerical simulation, and demonstrate that the linear reduced-order observer-based response system is better than the full-order observer-based one.

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25

Peresada, S. M., Y. O. Nikonenko, S. M. Kovbasa, D. I. Rodkin, and O. I. Kiselychnyk. "Observer-based speed estimation for vector controlled induction motors." Tekhnichna Elektrodynamika 2022, no. 1 (January 24, 2022): 25–32. http://dx.doi.org/10.15407/techned2022.01.025.

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A speed observer for field-oriented controlled induction drives is presented. The proposed solution exploits the concept of the classic full-order flux observer which is adaptive to the rotor resistance variations. Due to the structural similarity of the rotor speed and active rotor resistance in motor model, the speed observer can be designed using similar structure. The observer guarantees local asymptotic estimation of the rotor fluxes, stator currents and rotor speed in all operating conditions, excluding DC stator excitation. The stability properties of the observer are studied using Lyapunov’s second method. It is experimentally shown that the observer provides an acceptable dynamics of the speed estimation if speed is slowly varying. The proposed observer is suitable for the applications with medium requirements for speed regulation performance. References 13, figures 5.

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26

Iwai, Z., M. Ishitobi, and M. Hino. "Design of an Adaptive Pole Placement Control System Using Adaptive Observer." IFAC Proceedings Volumes 21, no. 9 (August 1988): 157–62. http://dx.doi.org/10.1016/s1474-6670(17)54718-7.

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27

He, Shuping, and Fei Liu. "Adaptive Observer-Based Fault Estimation for Stochastic Markovian Jumping Systems." Abstract and Applied Analysis 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/176419.

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This paper studies the adaptive fault estimation problems for stochastic Markovian jump systems (MJSs) with time delays. With the aid of the selected Lyapunov-Krasovskii functional, the adaptive fault estimation algorithm based on adaptive observer is proposed to enhance the rapidity and accuracy performance of fault estimation. A sufficient condition on the existence of adaptive observer is presented and proved by means of linear matrix inequalities techniques. The presented results are extended to multiple time-delayed MJSs. Simulation results illustrate that the validity of the proposed adaptive faults estimation algorithms.

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28

Ahmed-Ali, Tarek, Qinghua Zhang, Fouad Giri, and Xingwen Liu. "Transforming Time-Delay System Observers to Adaptive Observers." IFAC-PapersOnLine 53, no. 2 (2020): 1525–29. http://dx.doi.org/10.1016/j.ifacol.2020.12.2011.

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29

KAKIZOE, Yuki, Hisakazu NAKAMURA, and Hirokazu NISHITANI. "Remote Hybrid Controller with Adaptive Environment Observer." SICE Journal of Control, Measurement, and System Integration 1, no. 6 (2008): 443–51. http://dx.doi.org/10.9746/jcmsi.1.443.

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30

El magri, A., F. Giri, and A. El Fadili. "An Interconnected Adaptive Observer for PMS Motors." IFAC Proceedings Volumes 45, no. 21 (2012): 610–15. http://dx.doi.org/10.3182/20120902-4-fr-2032.00107.

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31

Bobtsov, Alexey, Anton Pyrkin, Nikolay Nikolaev, and Olga Slita. "ADAPTIVE OBSERVER DESIGN FOR CHAOTIC DUFFING SYSTEM." IFAC Proceedings Volumes 41, no. 2 (2008): 10160–65. http://dx.doi.org/10.3182/20080706-5-kr-1001.01719.

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32

Yuan, Zhi, Li Na Wu, Zheng Fang Wang, and Jie Liu. "Robust Fault Estimation Based on Adaptive Observer." Advanced Materials Research 791-793 (September 2013): 888–91. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.888.

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This paper investigates the adaptive observer-based robust fault estimation problem for linear uncertain systems with disturbances. Sufficient conditions for the existence of such a fault estimation observer are given in terms of matrix inequalities. The solution is obtained by the linear matrix inequality (LMI) technique. An example is given to demonstrate the effectiveness of the proposed approach.

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33

FUKAO, Takanori, and Norihiko ADACHI. "Observer-based Adaptive Control of Nonlinear Systems." Transactions of the Society of Instrument and Control Engineers 31, no. 9 (1995): 1351–57. http://dx.doi.org/10.9746/sicetr1965.31.1351.

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34

Smogeli, Øyvind N., and Asgeir J. Sørensen. "ADAPTIVE OBSERVER DESIGN FOR A MARINE PROPELLER." IFAC Proceedings Volumes 39, no. 1 (2006): 326–31. http://dx.doi.org/10.3182/20060329-3-au-2901.00047.

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35

SUGIE, Hiroshi, Takashi IWASAKI, Hideo NAKAGAWA, and Seido KOHDA. "Adaptive Lost Motion Compensation Using Disturbance Observer." Transactions of the Japan Society of Mechanical Engineers Series C 74, no. 739 (2008): 619–25. http://dx.doi.org/10.1299/kikaic.74.619.

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36

Yin, Shen, Xuebo Yang, and Hamid Reza Karimi. "Data-Driven Adaptive Observer for Fault Diagnosis." Mathematical Problems in Engineering 2012 (2012): 1–21. http://dx.doi.org/10.1155/2012/832836.

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This paper presents an approach for data-driven design of fault diagnosis system. The proposed fault diagnosis scheme consists of an adaptive residual generator and a bank of isolation observers, whose parameters are directly identified from the process data without identification of complete process model. To deal with normal variations in the process, the parameters of residual generator are online updated by standard adaptive technique to achieve reliable fault detection performance. After a fault is successfully detected, the isolation scheme will be activated, in which each isolation observer serves as an indicator corresponding to occurrence of a particular type of fault in the process. The thresholds can be determined analytically or through estimating the probability density function of related variables. To illustrate the performance of proposed fault diagnosis approach, a laboratory-scale three-tank system is finally utilized. It shows that the proposed data-driven scheme is efficient to deal with applications, whose analytical process models are unavailable. Especially, for the large-scale plants, whose physical models are generally difficult to be established, the proposed approach may offer an effective alternative solution for process monitoring.

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37

Chen, Yi-feng, and Tsutomu Mita. "Sliding Mode Control with Adaptive VSS Observer." IEEJ Transactions on Electronics, Information and Systems 111, no. 10 (1991): 514–22. http://dx.doi.org/10.1541/ieejeiss1987.111.10_514.

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38

Traore, D., J. De Leon, A. Glumineau, and L. Loron. "Adaptive interconnected observer for sensorless induction motor." International Journal of Control 82, no. 9 (July 15, 2009): 1627–40. http://dx.doi.org/10.1080/00207170802653719.

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39

Jin Young Choi and J. A. Farrell. "Adaptive observer backstepping control using neural networks." IEEE Transactions on Neural Networks 12, no. 5 (2001): 1103–12. http://dx.doi.org/10.1109/72.950139.

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40

Bullinger, Eric, Achim Ilchmann, and Frank Allgöwer. "A Simple Adaptive Observer for Nonlinear Systems." IFAC Proceedings Volumes 31, no. 17 (July 1998): 781–86. http://dx.doi.org/10.1016/s1474-6670(17)40434-4.

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41

Sauter, D., C. Aubrun, and D. Theilliol. "Adaptive State Observer Design for Fault Diagnosis." IFAC Proceedings Volumes 31, no. 18 (July 1998): 399–403. http://dx.doi.org/10.1016/s1474-6670(17)42024-6.

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42

Duarte-Mermoud, Manuel A. "A contribution on the parallel adaptive observer." Journal of the Franklin Institute 338, no. 1 (January 2001): 69–81. http://dx.doi.org/10.1016/s0016-0032(00)00065-x.

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43

Wang, H., and S. Daley. "Fault Diagnosis Using Adaptive Observer Based Techniques." IFAC Proceedings Volumes 29, no. 1 (June 1996): 6371–76. http://dx.doi.org/10.1016/s1474-6670(17)58703-0.

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44

Jiang, Bin, and Marcel Staroswiecki. "Adaptive observer design for robust fault estimation." International Journal of Systems Science 33, no. 9 (January 2002): 767–75. http://dx.doi.org/10.1080/00207720210144776.

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45

Ekramian, M., F. Sheikholeslam, S. Hosseinnia, and M. J. Yazdanpanah. "Adaptive state observer for Lipschitz nonlinear systems." Systems & Control Letters 62, no. 4 (April 2013): 319–23. http://dx.doi.org/10.1016/j.sysconle.2013.01.002.

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46

Fradkov, Alexander L., Henk Nijmeijer, and Alexey Yu Markov. "On adaptive observer-based synchronization for communication." IFAC Proceedings Volumes 32, no. 2 (July 1999): 2029–34. http://dx.doi.org/10.1016/s1474-6670(17)56344-2.

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47

Ahmed-Ali, Tarek, Fouad Giri, Miroslav Krstic, Laurent Burlion, and Françoise Lamnabhi-Lagarrigue. "Adaptive observer design with heat PDE sensor." Automatica 82 (August 2017): 93–100. http://dx.doi.org/10.1016/j.automatica.2017.04.030.

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48

Zhang, Qinghua, Fouad Giri, and Tarek Ahmed-Ali. "Regularized Adaptive Observer to Address Deficient Excitation." IFAC-PapersOnLine 52, no. 29 (2019): 251–56. http://dx.doi.org/10.1016/j.ifacol.2019.12.658.

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49

Yeon-Chan Hong, Jong-Hwan Kim, and Keh-Kun Choi. "Discrete adaptive observer with exponential weighting properties." IEEE Transactions on Automatic Control 34, no. 2 (1989): 229–31. http://dx.doi.org/10.1109/9.21108.

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50

Minamide, N., P. N. Nikiforuk, and M. M. Gupta. "Design of a reduced-order adaptive observer." IEE Proceedings D Control Theory and Applications 133, no. 3 (1986): 133. http://dx.doi.org/10.1049/ip-d.1986.0018.

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