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Design of the multi‐objective constrained nonlinear robust excitation controller with extended Kalman filter estimates of all state variables
Author(s) -
Zhifeng Gu,
Guixin Yang,
Changqing Zhu,
Tianzhang Shao
Publication year - 2015
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.3104
Subject(s) - control theory (sociology) , robustness (evolution) , nonlinear system , weighting , state variable , kalman filter , robust control , linear matrix inequality , controller (irrigation) , computer science , engineering , control system , mathematics , mathematical optimization , control (management) , medicine , agronomy , biochemistry , chemistry , physics , radiology , quantum mechanics , artificial intelligence , biology , electrical engineering , gene , thermodynamics
Summary A new optimal back‐stepping robust adaptive control method for the military moving power station (MMPS) excitation system is proposed in this paper. Through the extended Kalman filter estimates of the state variables, the tracking of the operating point, and the back‐stepping technique, the proposed controller has been shown to improve system robustness to disturbances and dynamic uncertainties and minimise the effect of disturbances by solving the linear matrix inequality to obtain the optimal control law on all operating points. The simulation and experimental results show that the proposed control strategy can enhance the transient stability of the MMPS excitation system more effectively than other methods and can optimise the convergence rates of the state variables by modifying the values of the weighting matrices. Moreover, the terminal voltage of the MMPS can be sampled quickly by alternating current (AC) tracking comparison. Copyright © 2013 John Wiley & Sons, Ltd.