AJOR  Vol.2 No.3 , September 2012
Dynamical Adaptive Particle Swarm Algorithm and Its Application to Optimization of PID Parameters
Author(s) Jimin Li, Guolin Yu
ABSTRACT
Based on a new adaptive Particle Swarm Optimization algorithm with dynamically changing inertia weight (DAPSO), It is used to optimize parameters in PID controller. Compared to conventional PID methods, the simulation shows that this new method makes the optimization perfectly and convergence quickly.

Cite this paper
J. Li and G. Yu, "Dynamical Adaptive Particle Swarm Algorithm and Its Application to Optimization of PID Parameters," American Journal of Operations Research, Vol. 2 No. 3, 2012, pp. 448-451. doi: 10.4236/ajor.2012.23053.
References
[1]   J. Kennedy and R. Eberhert, “Particle Swarm Optimization,” IEEE International Conference on Neural Networks, IEEE Service Center Press, IV. Piscataway, New Jersey, 1995, pp. 1942-1948.

[2]   C. Elegbede, “Structural Reliability Assessment Based on Particles Swarm Optimization,” Structural Safety, Vol. 27, No. 2, 2005, pp. 171-186. doi:10.1016/j.strusafe.2004.10.003

[3]   J. Pobinson and Y. Rahmat-Samii, “Particle Swarm Optimization in Electromagnetics,” IEEE Transactions on Antennas and Propagation, Vol. 52, No. 2, 2004, pp. 397-406. doi:10.1109/TAP.2004.823969

[4]   A. Salman, I. Ahmad and S. Al-Madani, “Particle Swarm Optimization for Task Assignment Problem,” Microprocessors and Microsystems, Vol. 26, No. 8, 2002, pp. 363-371. doi:10.1016/S0141-9331(02)00053-4

[5]   Y. Shi and R. Eberhart, “Empirical Study of Particle Swarm Optimization,” International Conference on Evolutionary Computation, IEEE Service Center Press, Washington DC, 1999, pp. 1945-1950.

[6]   Y. Shi and R. Eberhart, “Fuzzy Adaptive Particle Swarm Optimization,” The IEEE Congress on Evolutionary Compution, IEEE Service Center Press, San Francisco, 2001, pp. 101-106.

[7]   R. Eberhart and Y. Shi, “Tracking and Optimizing Dynamic Systems with Particle Swarm,” The IEEE Congress on Evolutionary Computation, IEEE Service Center Press, San Francisco, 2001, pp. 94-100.

[8]   J. M. Li, C. M. Lei and Y. Qiao, “Based on Expectations of Survival Rate Dynamic Adaptive Particle Swarm Algorithm,” Journal of Ningxia University, Vol. 12, 2009, pp. 347-350.

[9]   Y. X. Yuan and W. Y. Sun, “Optimization Theory and Method,” Science Press, Beijing, 1999, pp. 69-75.

 
 
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