Abstract
Unmanned aerial vehicle (UAV) applications have evolved to a wide range of fields in the last decade. One of the main challenges in autonomous tasks is the UAV stability during maneuvers. Thus, attitude and position control play a crucial role in stabilizing the vehicle in the desired orientation and path. Many control techniques have been developed for this. However, proportional integral derivative (PID) controllers are often used due their structure and efficiency. Despite PID’s good performance, different requirements may be present at different mission stages. The main contribution of this research work is the development of a novel strategy based on a fuzzy-gain scheduling mechanism to adjust the PID controller to stabilize both position and altitude. This control strategy must be effective, simple, and robust to uncertainties and external disturbances. The Robot Operating System (ROS) integrates the proposed system and the flight control unit. The obtained results showed that the proposed approach was successfully applied to the trajectory tracking and revealed a good performance compared to conventional PID and in the presence of noises. In the tests, the position controller was only affected when the altitude error was higher, with an error of 2% lower.
Highlights
Unmanned aerial vehicles (UAVs) give new opportunities to the industry due to their flexibility of flight, efficient and easy deployment, and simple structure [1]
The authors evaluate the fuzzy schedule control usage to improve the performance of an altitude controller in a simulated environment
The authors evaluated the combined position and altitude gain, scheduling in the simulated environment from this step. This idea reduced the position controller effort when a high altitude error was observed while still producing an adequate response otherwise
Summary
Unmanned aerial vehicles (UAVs) give new opportunities to the industry due to their flexibility of flight, efficient and easy deployment, and simple structure [1]. Note that the features added by the second fuzzy gain scheduler, where the altitude error is used to control the position performance, are not present in other implementations [16,29,32,37,40–45] This fuzzy controller allows changing performance following the UAV application requirements. The main contribution of this research work is the proposition of a novel strategy based on a fuzzy-gain scheduling mechanism to adjust the PID controller to stabilize both position and altitude control This control strategy must be effective, simple, and robust to uncertainties and external disturbances. Proposition of a novel PID-gain schedule through the use of a fuzzy logic scheme to stabilize the position and altitude controller of a UAV; Devise a strategy to tune Fuzzy PID controllers, considering environmental conditions.
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