Disturbance-Rejection-Based Optimized Robust Adaptive Controllers for UAVs

Most applications for small unmanned aerial vehicles (sUAVs) have a critical need for appropriate position and attitude control in environments with extreme external dynamic disturbances such as wind gusts. Moreover, to maximize flight time, UAVs have to operate within strict constraints on payload and under computational efficiency. This article presents an optimized robust adaptive controller for a UAV in the presence of realistic wind gusts that are flying in an urban environment at an altitude lower than 400 ft. The position controller is based on two degree-of-freedom proportional-integral-derivative controller tuned with particle swarm optimization, while the attitude controll is based on a robust adaptive integral backstepping controller. By assuming the knowledge of the predetermined limits of the external and unstructured disruptions (for example, wind gusts) at low altitude, a guaranteed quality of transient and steady-state tracking performance were attained. The aerodynamics, wind gust model, and control modules are integrated into a six-degree-of-freedom UAV with a fully nonlinear robust adaptive controller. Optimal power is obtained for UAVs using the radial inflow model in the presence of wind gusts that are compared with the simplified model. Two case studies were performed systematically for two representative flight paths, namely, up-cruise-down and circular paths. The simulation results demonstrate the robustness and adaptive property of controllers against wind gusts. These results are useful for a variety of UAV applications, e.g. accurate trajectory tracking and autonomous waypoint navigation without loss of performance in the presence of wind disturbances under computational efficacy.

Automated summary

This article presents an optimized robust adaptive controller for small unmanned aerial vehicles (sUAVs) flying in urban environments under realistic wind gusts, showcasing its robustness and adaptability against disturbances. Simulation results demonstrate the controller's effectiveness in maintaining performance during flight paths with wind disturbances, making it useful for various UAV applications.