Real time fuzzy controller for quadrotor stability control
Document Type
Conference Proceeding
Publication Date
1-1-2014
Abstract
© 2014 IEEE. In this paper, we develop an intelligent neuro-fuzzy controller by using adaptive neuro fuzzy inference system (ANFIS) techniques. We begin by starting with a standard proportional-derivative (PD) controller and use the PD controller data to train the ANFIS system to develop a fuzzy controller. We then propose and validate a method to implement this control strategy on commercial off-the-shelf (COTS) hardware. Using model based design techniques, the models are implemented on an embedded system. This enables the deployment of fuzzy controllers on enthusiast-grade controllers. We evaluate the feasibility of the proposed control strategy in a model-in-the-loop simulation. We then propose a rapid prototyping strategy, allowing us to deploy these control algorithms on a system consisting of a combination of an ARM-based microcontroller and two Arduino-based controllers.
Publication Title
IEEE International Conference on Fuzzy Systems
Recommended Citation
Bhatkhande, P.,
&
Havens, T.
(2014).
Real time fuzzy controller for quadrotor stability control.
IEEE International Conference on Fuzzy Systems, 913-919.
http://doi.org/10.1109/FUZZ-IEEE.2014.6891787
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/10484