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ABSTRACT This paper describes the actions taken to optimize the execution time of an attitude control of a quadrotor. An examination of the linear quadratic regulator (LQR) control method reveals the chance to replicate its performance through polynomial estimation. The optimized method is set up into a National Instruments sbRIO 9632 embedded acquisition and control board where it reduces execution time by a factor of ten while still working inside 2.5x10-5radians of the original controller technique. 1. INTRODUCTION The quadrotor was modeled as a principal mass with motors radiating collectively, as shown by Fig 1. Figure 1. Quadrotor diagram: Arrows indicate direction of rotor rotation. Roll (П•) is turning about the x-axis, pitch (Оё) is turning about the y-axis, and yaw (П$) is turning about the z-axis. The machine dynamics were fully explained by the set of nonlinear equations as given by Bouabdallah  in eqn. (1-6) below. The inputs to the system were defined in eqn. (7-10) while the gyroscopic disturbance was given by eqn. (11) in which the system factors are listed in Table 1. The system dynamics were put into state space form to facilitate control design and craft simulation. The states were arranged as in eqn. (12) which resulted in the state vector in eqn. (13). The rotational facets of the system were then represented as a subset of the nonlinear model. The rotational components were given by eqn. (14-17) , Where the time variant elements a-c of the A matrix were given by eqn. (18-20). Notice the A matrix in fact diverse with time since the machine dynamics were nonlinear, but the employed control method recalculated the matrices every millisecond. In th...