Background/Objectives: Design and development of an optimal control system for a quadcopter unmanned aerial vehicle (UAV). Methods/Statistical Analysis: The 6DOF quad copter state-space models was used for Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) simulations in MATLAB/Simulink. The simulations produced satisfactory results, which have been presented. Findings: A comparison between Low Pass Filter (LPF) and Kalman filter is also shown which shows that LQR is useless in presence of noise hence LQG was employed in such a situation. Application/Improvements: The optimal control system for quadcopter was successfully developed, which can be practically implemented on an actual quadcopter for stable unmanned flight of the aerial vehicle.
Keywords
Control, DOF, GPS, LQR, LQG, LPF, Quad-Copter, UAV.
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