Author(s)

Zhenghang Guo

Corresponding Author

Zhenghang Guo

Abstract

This chapter introduces an Adaptive Neuro-Fuzzy Inference System (ANFIS) integrated with a BP-PID algorithm, combining neural networks with fuzzy control. The system optimizes the fuzzy PID controller's parameters using neural networks and is tested through simulations. Compared to traditional PID and Adaptive Factor Fuzzy PID (AFPID) methods, the BP-PID algorithm demonstrates superior performance, particularly in reducing overshoot and maintaining stable control across various scenarios. The results validate BP-PID as an effective method for enhancing aircraft control.

Keywords

PID controller, Fuzzy logic, ANFIS, Quadcopter control