Towards evaluation of the PID criteria based UAVs observation and tracking head within resizable selection by COA algorithm
Noorulden Basil, Hamzah M. Marhoon
Abstract
The study of unmanned systems has garnered significant academic attention worldwide. The advancements in tracking technologies, particularly the unmanned aerial vehicle (UAV) developed by the US Air Force, have motivated scientists to extensively explore this field due to the abundance of available aerial resources. However, the UAV’s effectiveness in motion is influenced by its three fundamental motions: pitch, roll, and yaw. To address this, scientists have been developing optimization algorithms and models to enhance the UAV’s performance. Nonetheless, in practical scenarios, each motion requires specific measurements, and their relative importance varies. This presents several challenges, including the existence of multiple criteria for selecting optimization values, determining the criteria’s significance, and evaluating trade-offs between performance across different optimization cases. Consequently, the selection and evaluation of UAV motion control algorithms becomes complex. This study proposes a novel selection process that employs the cuckoo optimization algorithm (COA) and real measured resizable margins for goal detection instead of traditional fixed-size evaluation criteria. The framework consists of enhancing PID motion gains using the COA algorithm, focusing on altitude and attitude functional PID controllers. The results of the selection process demonstrate the significance of various criteria for different motions. Rigorous evaluation and analysis were conducted to validate the proposed research framework.