Robust control for a drone quadrotor using fuzzy logic-based fast terminal sliding mode control

In this article, we present a robust control strategy for a drone quadrotor, a multi-input multi-output complex and nonlinear system. Our approach combines a fast terminal sliding mode controller with Takagi-Sugeno fuzzy logic to achieve effective control. First, we study the mathematical model of the quadrotor drone. Then, we introduce a robust fast terminal sliding mode controller for the quadrotor system. This methodology requires the complete state of the system for robust control, which is not often directly observable. To overcome this challenge, we use a triangular observer to estimate the hidden states. Additionally, to attenuate the chattering phenomenon that results from sliding mode control, we employ Takagi-Sugeno fuzzy logic to approximate the additive control commands, thus reducing external disturbances. Furthermore, we introduce the Particle Swarm Optimization approach to improve the control accuracy by optimizing the main coefficients that significantly affect the efficiency of the fuzzy logic method, while ensuring the system stability constraints studied using the Lyapunov approach. Our simulations validate the effectiveness and robustness of the proposed control strategy, demonstrating significant improvements in control performance under various conditions.