PID Parameters Tuning Based on a Self-Adaptive Immunity Ant Colony Algorithm

DOI

10.2991/eeic-13.2013.67How to use a DOI?

Keywords

Particle swarm optimization; Immune algorithm; IPSO; PID Parameters Tuning

Abstract

For the disadvantages of being easy to fall into premature of particle swarm optimization and the lengthy process of immune algorithm, putting the immunization information processing mechanisms of the immune system into PSO algorithm. A particle swarm algorithm based on immune selection (IPSO) was proposed, and its application to the parameter tuning and self-adaption in PID controllers, and designing the PID controller parameters. Simulating by MATLAB, experimental results showed that the algorithm can solve the problem of PSO algorithm premature convergence, and applying to self-tuning PID controller.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuying Shao
AU  - Zhengquan Lv
AU  - Li Deng
AU  - Aiping Wang
PY  - 2013/12
DA  - 2013/12
TI  - PID Parameters Tuning Based on a Self-Adaptive Immunity Ant Colony Algorithm
BT  - Proceedings of the 3rd International Conference on Electric and Electronics
PB  - Atlantis Press
SP  - 289
EP  - 292
SN  - 1951-6851
UR  - https://doi.org/10.2991/eeic-13.2013.67
DO  - 10.2991/eeic-13.2013.67
ID  - Shao2013/12
ER  -