Hybrid ANFIS-ant colony based optimisation for quadrotor trajectory tracking control

作     者：Selma, Boumediene Chouraqui, Samira Abouaissa, Hassane 

作者机构：Univ Sci & Technol Oran USTOMB Dept Informat Oran 31000 Algeria Univ Artois EA 3926 Lab Genie Informat & Automat Artois LGI2A F-62400 Bethune France 

出 版 物：《INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL》 (国际建模、识别与控制杂志)

年 卷 期：2020年第34卷第1期

页      面：13-25页

核心收录：

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：UAV unmanned aerial vehicle intelligent control ANFIS adaptive-network-based fuzzy inference system ACO ant colony optimisation 

摘      要：This study proposes a robust, accurate and intelligent control for trajectory tracking of a three degree of freedom quadrotor unmanned aerial vehicle (UAV). The controller is based on adaptive-network-based fuzzy inference system (ANFIS) and ant colony optimisation (ACO) algorithm. Intelligent control such as fuzzy logic is a suitable choice for controlling nonlinear systems. The ANFIS controller is used to reproduce the reference trajectory of the quadrotor in 2-D vertical plane. The ACO algorithm provides an automatic adjustment of ANFIS parameters in order to reduce learning errors and improve the quality of the controller. To evaluate the performance of the proposed ANFIS controller tuned by ACO, it is compared with ANFIS and proportional-integral-derivative (PID) controllers. As expected, the hybrid ANFIS-ACO controller gives more satisfactory results than the other methods already developed in the same study.