Abstract
In this study, the nondominated sorting genetic algorithm (NSGA-II) is used to obtain the optimized proportional-integral-derivative (PID) gain value that can quickly recover the motion of a quadcopter after a disturbance. Prior to PID control, the four-rotor quadcopter interval was defined using computational fluid dynamics (CFD). Through the definition of this model, the PID control algorithm was generated. To construct a response surface model, D-optimal programming was used for the generation of experimental points. For this purpose, a gain value that satisfies both the roll and altitude PID gain values is obtained. Using the NSGA-II, the gain value of shorten time of the quadcopter motion control can be optimized.
| Original language | English |
|---|---|
| Pages (from-to) | 673-679 |
| Number of pages | 7 |
| Journal | Transactions of the Korean Society of Mechanical Engineers, A |
| Volume | 39 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 2015 Jul |
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All Science Journal Classification (ASJC) codes
- Mechanical Engineering
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Approximate multi-objective optimization of a quadcopter through proportional-integral-derivative control. / Yoon, Jaehyun; Lee, Jongsoo.
In: Transactions of the Korean Society of Mechanical Engineers, A, Vol. 39, No. 7, 07.2015, p. 673-679.Research output: Contribution to journal › Article
TY - JOUR
T1 - Approximate multi-objective optimization of a quadcopter through proportional-integral-derivative control
AU - Yoon, Jaehyun
AU - Lee, Jongsoo
PY - 2015/7
Y1 - 2015/7
N2 - In this study, the nondominated sorting genetic algorithm (NSGA-II) is used to obtain the optimized proportional-integral-derivative (PID) gain value that can quickly recover the motion of a quadcopter after a disturbance. Prior to PID control, the four-rotor quadcopter interval was defined using computational fluid dynamics (CFD). Through the definition of this model, the PID control algorithm was generated. To construct a response surface model, D-optimal programming was used for the generation of experimental points. For this purpose, a gain value that satisfies both the roll and altitude PID gain values is obtained. Using the NSGA-II, the gain value of shorten time of the quadcopter motion control can be optimized.
AB - In this study, the nondominated sorting genetic algorithm (NSGA-II) is used to obtain the optimized proportional-integral-derivative (PID) gain value that can quickly recover the motion of a quadcopter after a disturbance. Prior to PID control, the four-rotor quadcopter interval was defined using computational fluid dynamics (CFD). Through the definition of this model, the PID control algorithm was generated. To construct a response surface model, D-optimal programming was used for the generation of experimental points. For this purpose, a gain value that satisfies both the roll and altitude PID gain values is obtained. Using the NSGA-II, the gain value of shorten time of the quadcopter motion control can be optimized.
UR - http://www.scopus.com/inward/record.url?scp=84962687203&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84962687203&partnerID=8YFLogxK
U2 - 10.3795/KSME-A.2015.39.7.673
DO - 10.3795/KSME-A.2015.39.7.673
M3 - Article
AN - SCOPUS:84962687203
VL - 39
SP - 673
EP - 679
JO - Transactions of the Korean Society of Mechanical Engineers, A
JF - Transactions of the Korean Society of Mechanical Engineers, A
SN - 1226-4873
IS - 7
ER -