International Journal on Drones

An adaptive robust nonlinear control system for multi-copter unmanned aerial vehicles (UAVs) trajectory tracking and obstacle avoidance is presented in this research. The suggested approach addresses nonlinear dynamics and environmental uncertainties by combining adaptive disturbance estimates with constraint-based control.

The rapid evolution of unmanned aerial vehicles (UAVs), commonly referred to as drones, has transformed numerous domains — from military surveillance and logistics to precision agriculture and atmospheric research.

The integration of Internet of Things (IoT) technology with drone systems has revolutionized precision agriculture, offering innovative solutions to address the inefficiencies and environmental concerns linked to conventional pesticide application.

Electronic drones, commonly referred to as Unmanned Aerial Vehicles (UAVs), have transitioned from exclusively military platforms to indispensable tools across commercial, scientific, industrial, and recreational domains.

The integration of Internet of Things (IoT) technology into precision agriculture has transformed pesticide application strategies, enabling resource-efficient and environmentally sustainable practices.

Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity.