Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV

Area of Science:

• Robotics and Control Systems
• Aerospace Engineering
• Intelligent Control

Background:

• Tri-rotor unmanned aerial vehicles (UAVs) require advanced control for stable flight.
• Existing adaptive controllers face challenges in achieving optimal performance and rapid stabilization.
• Brushless direct current (BLDC) motors are crucial for UAV maneuverability and altitude control.

Purpose of the Study:

• To propose a novel fuzzy hybrid control scheme for stabilizing tri-rotor UAVs.
• To enhance the adaptive gains of a regulation pole-placement tracking (RST) controller using fuzzy logic.
• To validate the effectiveness of the proposed controller against existing methods.

Main Methods:

• Development of a fuzzy hybrid scheme integrating a fuzzy logic controller with an RST controller and model reference adaptive control (MRAC).
• Fine-tuning of RST controller adaptive gains via fuzzy logic.
• Implementation of an MRAC-based MIT rule for system stability analysis.
• Simulation of nonlinear flight dynamics, including translational and rotational velocities, using MATLAB.

Main Results:

• The proposed fuzzy hybrid controller demonstrates superior transient performance compared to the existing adaptive RST controller.
• The new algorithm achieves zero steady-state error, indicating precise control.
• Fast convergence towards stability is observed, highlighting the controller's efficiency.

Conclusions:

• The novel fuzzy hybrid control scheme offers significant improvements in UAV stabilization.
• The integration of fuzzy logic with adaptive control provides robust performance for nonlinear flight dynamics.
• This approach represents a promising advancement for unmanned aerial vehicle control systems.