PID denetleyici optimizasyonu Üzerine uygulamasi

Particle swarm optimization (PSO) is a swarm based optimization algorithm to find an optimum solution of a problem. In the present study, a new approach to PSO algorithm is proposed. Instead of using only the best solution at each iteration, the worst solution is added to the algorithm to enhance th...

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Bibliographic Details
Published in2017 International Artificial Intelligence and Data Processing Symposium (IDAP) pp. 1 - 6
Main Authors GIdemen, Gokcen, Furat, Murat
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2017
Subjects
Algorithm design and analysis
Control systems
fitness function
Indexes
Optimization
Particle swarm optimization
Performance analysis
PID tuning
Tuning
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Summary:Particle swarm optimization (PSO) is a swarm based optimization algorithm to find an optimum solution of a problem. In the present study, a new approach to PSO algorithm is proposed. Instead of using only the best solution at each iteration, the worst solution is added to the algorithm to enhance the performance. A PID parameter tuning problem for a second-order system having noise at the output is taken into account. Both classical and proposed algorithm are applied to the control system and performance analysis is given in graphically and statistically. The results are showed that the proposed algorithm finds the optimum solution with less particles defined in the swarm.
DOI:10.1109/IDAP.2017.8090259