A Novel PID Controller Parameter Optimization Method

Article Preview

Abstract:

For the difficulties of PID controller parameter optimization, we have put forward a novel depiction method PPOGS (PID Parameters Optimization based on Glowworm Swarm). By combining the minimum error absolute time integral definition proportion, the objective optimal functions of integral and differential functions, this method can produce the optimal allocation with the help of the glowworm swarm algorithm which seeks solution to the objective function. At last, we use MATLAB to make a simulation experiment, conducting an in-depth investigation of the key factors influencing the method. The results have showed PPOGS has better adaptability compared with other methods Key words: PID controller; parameter optimization; glowworm swarm; simulation

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1077-1081

Citation:

Online since:

March 2015

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Yesil E, Guzelkaya M, Eksin I. Self tuning fuzzy PID type load and frequency controller[J]. Energy Conversion and Management, 2004, 45(3): 377-390.

DOI: 10.1016/s0196-8904(03)00149-3

Google Scholar

[2] Gu H P, Huang W J. A fuzzy-PID temperature controller[J]. Chinese Journal of Industry Control & Application, 2005, 24(8): 28-30.

Google Scholar

[3] Shang H, Chen Z M, Ren Y P. Parameter selection for a new class of nonlinear PID controller[J]. Control Theory & Applications, 2009, 26(4): 439-442.

Google Scholar

[4] Sun Y F, Zhang S Y, Zhou L. Adaptive active queue management of delay network based on fuzzy immune PID[J]. Journal of China Institute of Communications, 2005, 26(8): 36-43.

Google Scholar

[5] Piao H G, Wang Z X, Zhang H Q. Nonlinear control system of PID neural network based on cooperated particle swarm optimization[J]. Control Theory & Applications, 2009, 26(12): 1317-1324.

Google Scholar

[6] Peng P F, Lin Y P, Hu B, Zhang G F. Optimal PID Control of Self-Adapted Ant Colony Algorithm Based on Genetic Gene[J]. Acta Electronica Sinica, 2006, 34(6): 1109-1113.

DOI: 10.1109/csse.2008.760

Google Scholar

[7] Yang Z, Chen Z T, Fan Z P, Li X D. Tuning of PID controller based on improved particle-swarm-optimization[J]. Control Theory & Applications, 2010, 27(10): 1345-1352.

Google Scholar

[8] Zhou Y Q, Huang Z X, Liu H X. Discrete glowworm swarm optimization algorithm for TSP problem[J]. Acta Electronica Sinica, 2012, 40(6): 1164-1170.

Google Scholar

[9] Wang Y, Deng Y, Wang C. Fuzzy neural network PID controller design based on improved particle swarm optimization[J]. Control and Decision, 2012, 19(5): 761-764.

Google Scholar