期刊論文
| 學年 | 109 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2020-09-04 |
| 作品名稱 | New Fusion Algorithm-Reinforced Pilot Control for an Agricultural Tricopter UAV |
| 作品名稱（其他語言） | |
| 著者 | HK Tran; JS Chiou; VH Dang |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | Mathematics 8(9), 1499 |
| 摘要 | Currently, fuzzy proportional integral derivative (PID) controller schemes, which include simplified fuzzy reasoning decision methodologies and PID parameters, are broadly and efficaciously practiced in various fields from industrial applications, military service, to rescue operations, civilian information and also horticultural observation and agricultural surveillance. A fusion particle swarm optimization (PSO)–evolutionary programming (EP) algorithm, which is an improved version of the stochastic optimization strategy PSO, was presented for designing and optimizing controller gains in this study. The mathematical calculations of this study include the reproduction of EP with PSO. By minimizing the integral of the absolute error (IAE) criterion that is used for estimating the system response as a fitness function, the obtained integrated design of the fusion PSO–EP algorithm generated and updated the new elite parameters for proposed controller schemes. This progression was used for the complicated non-linear systems of the attitude-control pilot models of a tricopter unmanned aerial vehicle (UAV) to demonstrate an improvement on the performance in terms of rapid response, precision, reliability, and stability. |
| 關鍵字 | particle swarm optimization (PSO);evolutionary programming (EP);fuzzy control;proportional–integral–derivative controller;integral of absolute error (IAE) criterion;attitude control;tricopter unmanned aerial vehicle (UAV) |
| 語言 | en_US |
| ISSN | 2227-9717 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | CHE |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/121949 ) |