Complex intuitionistic fuzzy sets, which are distinguished by both membership and non-membership values, provide sophisticated decision-making tools by helping decision-makers better handle ambiguity, reluctance, and uncertainty in complex situations. In this paper, we introduce several novel operations on complex intuitionistic fuzzy sets, including a complex intuitionistic fuzzy distance measure, which is utilized to define \(\sigma\)-equalities of complex intuitionistic fuzzy sets. This method is applied to a decision-making scenario that takes place in the real world in order to show its practical value. This scenario illustrates the potential of complex intuitionistic fuzzy sets in tackling difficult and ambiguous choice issues with increased flexibility and accuracy. Finally, in order to demonstrate the efficacy of the suggested strategy, we compare it to other methods that have been taken in the past.

The market of Unmanned Aerial Vehicles (UAVs) for civil applications is extensively growing. Indeed, these airplanes are nowadays widely used in applications such as data gathering, agriculture monitoring and rescue. The UAVs are required to track a fixed or moving object, thus tracking control algorithms that ensure the system stability and that have a quick time response are developed. This paper tackles the problem of supervising a fixed target using a ϐixed wing UAV flying at a constant altitude and a constant speed. For that purpose, three control algorithms are developed. In all of the algorithms, the UAV is expected to hover around the target in a circular trajectory. Moreover, the three approaches are based upon a Lyapunov‑LaSalle stabilization method. The first tracking algorithm ensures the UAV to circle around the target however the path that the UAV will follow in order to join this pattern is not studied. In the second and third approach, two different techniques that allow the UAV to intercept its final circular pattern in the quickest possible time and thus follow the tangent to the circular pattern are presented. Simulation results that show and compare the performances of the proposed methods are presented.