Conference proceeding
Fuzzy logic-based self-tuning autopilots for trajectory tracking of a low-cost quadcopter: A comparative study
2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA), pp.64-69
International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA) (Surabaya, Indonesia., 15/10/2015 - 17/10/2015)
2015
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Abstract
In this work, we develop self-tuning PD-fuzzy autopilots for trajectory tracking of a low-cost Parrot AR.Drone2 quadcopter. We first recall the mathematical model of the system in terms of its multi-input, multi-output (MIMO) transfer function model acquired via system identification technique. Accordingly, we design three self-tuning autopilots by means of fuzzy inference systems to control the position of the drone in 3D space. This research serves as a preliminary study in our design process to investigate the feasibility of our fuzzy self-tuning autopilot before we can implement it into practice. We perform a systematic comparative study to highlight the effectiveness of our control algorithm with respect to fixed-gain autopilot as well as fuzzy logic controller.
Details
- Title
- Fuzzy logic-based self-tuning autopilots for trajectory tracking of a low-cost quadcopter: A comparative study
- Creators
- Fendy Santoso - University of New South WalesMatthew A. Garratt - University of New South WalesSreenatha G. Anavatti - University of New South Wales
- Publication Details
- 2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA), pp.64-69
- Conference
- International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA) (Surabaya, Indonesia., 15/10/2015 - 17/10/2015)
- Publisher
- IEEE
- Identifiers
- 991013092671402368
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Conference proceeding