abstract
- © Springer International Publishing Switzerland 2016.Artificial intelligence has opened new alternatives to control non-linear systems. One of the most important methods is the fuzzy logic controller, which is constructed with linguistic rules; however, it is normally based on the knowledge from human experts, so the linguistic rules and membership functions are not optimized. In the case of Quadrotors, it is important to acquire the knowledge from human experts because they are able to naturally describe the controller for this non-liner system by linguistic rules in a complete form but the memory space and processing time have to be minimum in the hardware implementation. Hence, a neuro fuzzy controller (ANFIS) is used in order to reduce the number of linguistic rules and membership functions and to preserve the surface between inputs and outputs in the controller for Quadrotors. Hence, the real time controller improves its response. This proposal keeps the basic idea of getting the knowledge from human experts and then ANFIS can be implemented in the real time hardware in the Quadrotor. The results show that this methodology is an excellent option to control Quadrotors.