Mini Drone Linear and Nonlinear Controller System Design and Analyzing

Abstract

Choosing the mini-drone for a specific payload for designing purposes is one of the most challenging for both cost and design purposes. It is important to develop and analyze the flight control systems of the quadcopter-type Parrot mini drone and how to make the drones more tolerant of adverse weather conditions. The main problem with any quadcopter is that it loses its balance when exposed to any external influence, even if that influence is weak. Where the controller is the most important part of the drone, six plane controllers cover the six degrees of freedom (6dof) in the movement of the drone. In our research, we have improved the height controller in the drone, thus improving the altitude controller by using (PD) and increasing the values of (Kp and Kd) in the altitude controller of the Parrot Mini Drone Mambo to make it more bearable to external influence and to maintain its altitude. We assumed that the aircraft was exposed to bad weather conditions, such as snowfall and dust, which led to an increase in the speed at which the drone fell. We also increased the free fall constant of the object in the simulation design of the drone from (-9.81 m/s2 to -12.81 m/s2) and used Matlab R2021a Simulink to undertake the tuning of the (Kp and Kd) values. This study yielded good results, as illustrated in the results section. Therefore, this research paper suggests adopting the PD controller in the altitude controller and the new values of Kp and Kd to make the drone more tolerant of weather conditions. We tested these results in practice and got good results.

Improving the Size of the Propellers of the Parrot Mini-Drone and an Impact Study on its Flight Controller System

“…Given a three-dimensional reference, an X-Y location, and altitude, which are all consistent in this task, it should be verified that it is stable when hovering. The mini-drone will only have a change of reference in the X-Y location while monitoring the path, which is developed and continuously updated by the path planning algorithm [9]. If we consider that the micro drone's camera should be facing down almost orthogonally during these motions in order to see the track in the correct orientation, we can expect modest pitch and roll angles.…”

Evaluation of Single and Dual image Object Detection through Image Segmentation Using ResNet18 in Robotic Vision Applications

“…The Arduino microcontroller board can operate in real-time by connecting to the MATLAB & Simulink program. While other research studies have proposed various designs for the system, such as micro-robotics [83], Microgrid [84], mini drone [85], DC motor control [86], [87], BLDC motor [88], lane-keeping control [89], and hexapod robot [90], none of them have focused on image processing. Nonetheless, these studies illustrate the potential applications of robotic vision design in different areas of robotics.…”

Design and Testing of a Pid Controller on a Parrot Minidrone

“…We are aware that non-linear models are excellent for simulations, but we do not want any non-linearities in our system for control design or linear analysis. We require a linear model to tune our six PID controllers, even though it is obviously less accurate than the non-linear model (Kadhim & Abdulsadda, 2022).…”