Optimal tuning of PID controller for AVR system using Modified particle swarm optimization

Proc. of the 11th WSEAS Int. Conf. on Neural Networks, NN '10, Proceedings of the 11th WSEAS Int. Conf. on Evolutionary Computing, EC '10, Proc. of the 11th WSEAS Int. Conf. on Fuzzy Systems, FS '10

Volumn , Issue , 2010, Pages 104-110

  Shabib, G ^a   Moslem, A G ^a   Rashwan, A M ^a  

^a SOUTH VALLEY UNIVERSITY   (Egypt)

Author keywords

AVR system; Particle swarm optimization; PID controller

Indexed keywords

AVR SYSTEM; FAST TUNING; HIGH-QUALITY SOLUTIONS; MODIFIED PARTICLE SWARM OPTIMIZATION; OPTIMAL TUNING; PERFORMANCE CRITERION; PID CONTROLLER; PID CONTROLLERS; POWER SYSTEMS; SIMULATION COMPARISON; TIME DOMAIN;

ALGORITHMS; CONTROLLERS; ELECTRIC CONTROL EQUIPMENT; FUZZY SETS; NEURAL NETWORKS; PROPORTIONAL CONTROL SYSTEMS; TIME DOMAIN ANALYSIS; TWO TERM CONTROL SYSTEMS;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 79952662155     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. H. Saadat, Power System Analysis. New York: McGraw Hill, 1999.
2. Q.H. Wu, B.W. Hogg, G.W. Irwin, A neural network regulator for turbogenerators, IEEE Trans. Neural Networks 3 (1992) 95-100.
3. A. Visioli, "Tuning of PID controllers with fuzzy logic," Proc. Inst. Elect. Eng. Contr. Theory Applicant., vol. 148, no. 1, pp. 1-8, Jan. 2001. (Pubitemid 32271942)
4. Ziegler JG, Nichols NB. Optimum settings for automatic controllers. Trans ASME 1942;64:759-68.
5. R.A. Krohling, J.P. Rey, Design of optimal disturbance rejection PID controllers using genetic algorithm, IEEE Trans. Evol. Comput. 5 (February) (2001) 78-82 (Pubitemid 32330499)
6. T. Kawabe and T. Tagami, "A Real-Coded Genetic Algorithm for Matrix Inequality Design Approach of Robust PID Controller with Two Degrees of Freedom", in Proc. 12th IEEE Int. Symp. Intell. Contr., Istanbul, Turkey, pp. 119-124, July 1997.
7. J. Kennedy, R.C. Eberhart, Particle swarm optimization, in: Proceedings of IEEE International Conference on Neural Networks, Perth, Australia, 1995, pp. 1942-1948.
8. th IEEE Int. Symp. Intell. Contr., Istanbul, Turkey, July 1997, pp. 125-130.
9. R. C. Eberhart and Y. Shi, "Comparison between Genetic Algorithms and Particle Swarm Optimization", in Proc. IEEE Int. Conf. Evol. Comput., Anchorage, AK, pp. 611-616, May 1998.
10. S.P. Ghoshal, Optimization of PID gains by particle swarm optimization in fuzzy based automatic generation control, Electr. Power Syst. Res. 72 (2004) 203-212.
11. Z.L. Gaing, A particle swarm optimization approach for optimum design of PID controller in AVR system, IEEE Trans. Energy Convers. 19 (June (2)) (2004) 384-391.