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This study investigates the longitudinal motion control of unmanned aerial vehicles through a simulation in MATLAB. The linear model of an unmanned aerial vehicle is applied to controllers to explicate the longitudinal motion of the unmanned aerial vehicle. The ideal performance for an unmanned aerial vehicle is to achieve the desired response instantly with 100% precision. However, currently available controllers need further improvements. Thus, a proportional-derivative linear quadratic regulator controller is developed and compared with a proportional-integral-derivative controller, a linear quadratic regulator controller, and a proportional linear quadratic regulator controller. The proportional-derivative linear quadratic regulator controller enhances the response of the system by reducing settling time by more than 95% compared with other available controllers. Additionally, the proportional-derivative linear quadratic regulator improves the root mean square error by almost 50% compared with the proportional linear quadratic regulator controller and improves rise time by almost 96% with reasonable overshoot.

This paper describes studies the longitudinal motion control of unmanned aerial vehicles (UAVs) by using a proportional-integral-derivative (PID) controller, linear-quadratic-regulator (LQR) controller, and P-LQR controller. The non-linear model of the motion is changed into a linear model and is implemented in the controllers to elucidate the longitudinal motion of UAVs. The control performance of the aircraft improves when the UAV reaches the desired response instantaneously and precisely. However, the performance of currently available controllers is not ideal, and a 10% improvement in controller performance can lead to a significant effect. Thus, the P-LQR controller is developed. This controller significantly improves the response times of the control system by at least 38.55% compared with other existing controllers. Hence, an alternative longitudinal motion control for UAVs has been proposed.