Hybrid ANFIS-ant colony based optimisation for quadrotor trajectory tracking control Online publication date: Thu, 06-Aug-2020
by Boumediene Selma; Samira Chouraqui; Hassane Abouaïssa
International Journal of Modelling, Identification and Control (IJMIC), Vol. 34, No. 1, 2020
Abstract: 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.
Online publication date: Thu, 06-Aug-2020
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Modelling, Identification and Control (IJMIC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com