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Article . 2021
License: CC BY NC
Data sources: Datacite
ZENODO
Article . 2021
License: CC BY NC
Data sources: Datacite
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Tuning PID Controller Bases on Random Search Algorithms

Authors: Dung Vuong Quoc; Thuy Tran Thi; Nguyet Do Thi Minh; Minh Nguyen Quang; Loi Nguyen Tien; Binh Nguyen Thi Thanh;

Tuning PID Controller Bases on Random Search Algorithms

Abstract

In this paper, we present two well known random search algorithms which are Genetic algorithm (GA) and Particle Swarm optimization (PSO) to find optimal parameters for PID controller for a model of DC motor is used as a plant. To test performance of GA and PSO algorithms, we compare them with the traditional Ziegler-Nichols method in term of performance indices. The simulation results show that Proportional Integral and Derivative controller (PID) designed by GA and PSO algorithms yields better results than the traditional method in terms of the performance index.

Keywords

Tuning PID; GA algorithm; PSO algorithm; Ziegler-Nichols method; performance index; optimization.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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