Journal
NEUROCOMPUTING
Volume 124, Issue -, Pages 139-148Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2013.07.018
Keywords
AVR system; Parameter identification; Gravitational search algorithm; Piecewise function
Categories
Funding
- National Natural Science Foundation of China [51109088]
- Research Fund for the Doctoral Program of Higher Education of China [20110142120020]
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Heuristic optimization has shown its superiority in handling identification problem of complicated system, for methods based on heuristic optimization do not have special requirements on model structures of the target system. In this paper, a piecewise function based gravitational search algorithm (PFGSA) is proposed and applied in parameter identification of automatic voltage regulator (AVR) system. In the proposed algorithm, a piecewise function is designed as the gravitational constant function to replace the traditional exponential equation. The piecewise function provides more rational gravitational constant to control the convergence of algorithm, and thus excellent searching ability is likely to be achieved. Moreover a new weighted objective function is proposed in the identification frame. Comparative experimental studies are conducted to test the searching ability of PFGSA and to verify the performance of proposed identification strategy, while genetic algorithm, particle swarm optimization and GSA are employed for comparison. The experimental results show that PFGSA performs the best on term of accuracy and stability in the parameter identification of AVR system, and the proposed identification strategy is effective. (C) 2013 Elsevier B.V. All rights reserved.
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