Optimal Sliding Mode Control with PID Surface based Trajectory Control of Quadcopter for Wind Turbine Surface Damage Detection

Abstract

Unmanned aerial vehicles (UAVs) are aircraft that are able to fly without the need for a pilot, thanks to financial and technological breakthroughs. these UAVs have made a number of things possible, including mapping, aerial photography, video recording, pollution and land monitoring, wind turbine inspection, firefighting, agricultural applications, military activities, and more. The nonlinear, underactuated nature, instability, and uncertainty around the parameters make it difficult to manage the quadrotor's flight. In this research work, a quadrotor dynamic model is developed, and Optimal sliding mode control using the proportional integral derivative (PID) surface technique is applied to control the trajectory of quadrotor including its trajectory during wind turbine surface damage detection. The designed controller incorporates SMC with PID surface control method and quasi function to adequately reduce the chattering effect of sliding mode control. Additionally, image acquired from the quadrotor are train using Roboflow in YOLOv8. Particle swarm optimization (PSO) is used to optimize the controller parameters. Finally, the performance of designed controller tested under parameter variation and wind wind disturbance with designed specific trajectory of quadrotor during wind turbine surface damage detection. The simulation result shows that quadrotor can handle parameter variation and wind disturbance and able to follow the designed trajectory effectively. Also chattering effect due to conventional SMC is reduced effectively. In ream of image processing, the system able to identify damaged part of wind turbine with best performance of training and validation. Additionaly, the performance of the SMC with PID surface control is compared with SMC to the proposed controller shows robust performance.