Purpose Although windy weather conditions have a significant effect on the flight safety and stability of any aircraft, the fact that quadrotors are lighter than other aircraft makes them more sensitive to the wind. This study aims to examine the extent to which quadrotors and their sensors, which are used in many fields and whose use is expected to increase significantly in the future, are affected by wind. Design/methodology/approach Flight experiments were carried out on different routes assigned by using Pixhawk Holybro 4 and Radiolink flight controllers. In these flight experiments, quadrotors were exposed to winds at different speeds and directions. Findings In the flight experiments, the deviation amounts in the quadrotor’s route at which wind speed was determined, and it was seen that these deviations were very serious and affected the safe flight at high wind speeds. According to the sensor information obtained from both different quadrotors’ flight experiments at different wind speeds, it was determined that the wind decreased the sensors’ accuracy. Practical implications It is foreseen that the data obtained in this study will be a source to be used in the design of quadrotors to be used in public areas in the future and to take the wind into account for safe flight. Originality/value In this study, numerous flight tests were carried out experimentally at various speeds from low speeds to high speeds on different routes using different flight controllers. The deviation data on the obtained routes and the effect of the wind on the sensors are experienced in real atmospheric conditions.
Purpose This study aims to develop a quadrotor with a robust control system against weight variations. A Proportional-Integral-Derivative (PID) controller based on Particle Swarm Optimization and Differential Evaluation to tune the parameters of PID has been implemented with real-time simulations of the quadrotor. Design/methodology/approach The optimization algorithms are combined with the PID control mechanism of the quadrotor to increase the performance of the trajectory tracking for a quadrotor. The dynamical model of the quadrotor is derived by using Newton-Euler equations. Findings In this study, the most efficient control parameters of the quadrotor are selected using evolutionary optimization algorithms in real-time simulations. The control parameters of PID directly affect the controller’s performance that position error and stability improved by tuning the parameters. Therefore, the optimization algorithms can be used to improve the trajectory tracking performance of the quadrotor. Practical implications The online optimization result showed that evolutionary algorithms improve the performance of the trajectory tracking of the quadrotor. Originality/value This study states the design of an optimized controller compared with manually tuned controller methods. Fitness functions are defined as a custom fitness function (overshoot, rise-time, settling-time and steady-state error), mean-square-error, root-mean-square-error and sum-square-error. In addition, all the simulations are performed based on a realistic simulation environment. Furthermore, the optimization process of the parameters is implemented in real-time that the proposed controller searches better parameters with real-time simulations and finds the optimal parameter online.
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