Abstract
The unmanned aerial vehicles can have complicated dynamics and kinematics that governs the flight of such multirotor devices. PID type controllers are one of the most popular approaches with Raspberry Pi 3 platform for stability of the flight. However, in dynamic environment they are limited in performance and response times. The autonomous tuning of the controller parameters according to the state of the environment with assistance of the adaptive neuro-fuzzy inference system is a well known approach. This paper provides implementation details and feasibility of such a controller with Raspberry Pi 3 platform for use in geological wireless sensing environments. The proposed neuro-fuzzy controller is developed for a Raspberry Pi 3 platform and tested on a physical quadrotor drone and compared to the conventional PID controller during flight.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 435-445 |
| Number of pages | 11 |
| Journal | Analog Integrated Circuits and Signal Processing |
| Volume | 95 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jun 1 2018 |
Keywords
- ANFIS
- Control
- Drone stabilization
- Neuro-fuzzy
- Quadrotor
ASJC Scopus subject areas
- Signal Processing
- Hardware and Architecture
- Surfaces, Coatings and Films