Ant Colony Optimization of type-2 Fuzzy Helicopter Controller

被引：0
|
作者：
Rezoug, A. [1 ]
Achour, Z. [1 ]
Hamerlain, M. [1 ]
机构：
[1] Ctr Dev Adv Technol, Cite 20 Aout 1956,BP 17, Algiers 16303, Algeria
来源：
2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS IEEE-ROBIO 2014 | 2014年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Many works have been done for controlling nonlinear systems using bio-inspired methods. In this paper, we propose an optimal intelligent controller for an Unmanned Aerial Vehicle (UAV). The controller consists on a type-2 fuzzy system with defuzzifier step was determined through Ant Colony Optimization algorithm (ACO). It is known that, ACO and Particle Swarm Optimization (PSO) algorithm are the most powerful bio-inspired optimization methods. Then, performances of ACO and PSO were compared. All optimized controllers were applied to Birotor helicopter system. Simulations results were given to show superiority of ACO compared with PSO and the classical case (type-2 fuzzy controller without optimization).
引用
收藏
页码：1548 / 1553
页数：6
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