Intelligent Control of an Autonomous Octorotor Flight Drone Using Image-Based Visual Servoing (IBVS) Under Wind Disturbances

This paper presents a fuzzy-adaptive image-based visual servoing (FAIBVS) command and control system for an octorotor UAV that operates in both wind-disturbed (WD) and nominal circumstances. By combining image-based visual servoing (IBVS) with a fuzzy logic supervisor (FLS), the suggested approach ensures quick convergence while minimizing undue control effort by adaptively adjusting the visual interaction gain in real time depending on visual error dynamics within the camera field of view (CFOV). Additional stability and resilience against nonlinearities and outside disturbances are improved by a low-level fuzzy PD controller (FPDC). The Newton–Euler formulation is used to model the octorotor system, capturing its under actuated six-DOF dynamics. Our suggested approach (FAIBVS) performs better than classical IBVS and fixed-gain PD-IBVS strategies in terms of trajectory stability, balanced control effort, visual tracking accuracy, and wind disturbance (WD) rejection, according to extensive simulations carried out in a Python environment. These outcomes demonstrate how well the proposed command and control method works for dependable octorotor Unmanned Aerial Vehicle (OUAV) navigation in difficult conditions.