Ruofa Cheng
Nanchang Hangkong University, 330063, Nanchang, China
Jianchao Gao
Nanchang Hangkong University, 330063, Nanchang, China
Xinhong Yu
Nanchang Hangkong University, 330063, Nanchang, China
Hongfeng Deng
Nanchang Hangkong University, 330063, Nanchang, China
ABSTRACT
Excitation control system of synchronous generator is a strong nonlinearity, multi-variable, strong couple and time-varying control system. It is very difficult for traditional Proportional Integral Derivative (PID) to get good control performance. A new excitation control strategy based on PID controller and Cerebellar Model Articulation Controller (CMAC) is proposed in this study. To solve the problem of PID and CMAC compound controller multi-parameter setting, an Improved Multi-agent Genetic Algorithm (IMAGA) is presented. The PID parameters Kp, Ki, Kd and CMAC parameters η, α are regarded as a agent. Each agent continuously improves its fitness value through competition and cooperation between the other agents according to the objective function of Integral of Time-weighted Absolute value of the Error (ITAE). This algorithm adopts multi-agent coordinate optimization to realize the five parameters of Kp, Ki, Kd, η, αonline tuning. The simulations results show that the compound control scheme based on multi-agent genetic algorithm can improve the precision of excitation control, the speed of responding and has better dynamic and steady-state characteristics.
PDF References Citation
How to cite this article
Ruofa Cheng, Jianchao Gao, Xinhong Yu and Hongfeng Deng, 2013. Synchronous Generator Excitation System Optimization Control Based on Multi-agent Genetic Algorithm. Information Technology Journal, 12: 4959-4967.
DOI: 10.3923/itj.2013.4959.4967
URL: https://scialert.net/abstract/?doi=itj.2013.4959.4967
DOI: 10.3923/itj.2013.4959.4967
URL: https://scialert.net/abstract/?doi=itj.2013.4959.4967
REFERENCES
- Cheng, L., J.Y. Zhang, Y.Z. Sun, X.P. Guan, C. Wu and W.Y. Li, 2007. Closed-loop optimum design method for PID controller of excitation system in large-scale power system. Power Syst. Technol., 31: 49-53.
Direct Link - Cheng, R.F. and J. Liu, 2011. Design of multi-parameters optimization CMAC controller based on improved GA. Manuf. Autom., 33: 37-40.
Direct Link - He, H., J. Zhou, P. Kou and X. Zhang, 2010. Application study of tent mapping-based chaos adaptive PSO algorithm in excitation control system of synchronous generator. Power Syst. Technol., 35: 45-49.
Direct Link - Wang, X.H., T.F. Zhang and J.M. Xiao, 2007. Ship generator excitation control system based on rough set integrated with radial basis function networks. Power Syst. Technol., 31: 66-71.
Direct Link - Zeng, X.P., Y.M. Li, J. Wang, X.J. Zhang and Y.M. Zheng, 2008. Link-like agent genetic algorithm for feature selection based on competition strategy. J. Syst. Simul., 20: 1973-1979.
Direct Link - Zhong, W., J. Liu, M. Xue and L. Jiao, 2004. A multiagent genetic algorithm for global numerical optimization. IEEE Trans. Syst. Man Cybern., B: Cybern., 34: 1128-1141.
CrossRef