Study on an improved algorithm for optimization of PID parameters

Authors

  • Shaofei Wu Wuhan Institute of Technology

DOI:

https://doi.org/10.3991/ijoe.v12i02.5050

Keywords:

Improved ant colony algorithm, Genetic algorithm, Gauss mutation, PID, Optimization.

Abstract


The improved ant colony algorithm is the hybrid algorithm consisting of the genetic algorithm and ant colony algorithm convergence. Through the introduction of the gauss mutation, we achieve the goal of improving ant colony algorithm. Using coal-fired power plant unit as main steam temperature controlled object, we design the PID controller based on improved ant colony algorithm. And setting of PID parameters by Z - N method has carried on the comparative analysis of the main steam temperature control system. Simulation results show that PID optimization based on improved ant colony algorithm can greatly improve the dynamic performance of the control system. So we verify the sophistication and effectiveness of the algorithm.

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Published

2016-02-29

How to Cite

Wu, S. (2016). Study on an improved algorithm for optimization of PID parameters. International Journal of Online and Biomedical Engineering (iJOE), 12(02), pp. 58–60. https://doi.org/10.3991/ijoe.v12i02.5050

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Section

Papers