MULTIDISCIPLINARY DESIGN OPTIMIZATION OF UNMANNED AERIAL VEHICLES

Abstract

The increasing complexity of modern Unmanned Aerial Vehicle (UAV) missions has highlighted the need for advanced design methodologies that integrate multiple engineering disciplines into a unified optimization framework. Traditional sequential design approaches often fail to capture the strong interactions between aerodynamics, structures, propulsion, flight dynamics, and control systems, leading to suboptimal aircraft performance and extended development cycles. Multidisciplinary Design Optimization (MDO) has emerged as an effective engineering methodology that simultaneously considers these interdependent disciplines to achieve optimal system-level performance. This paper examines the principles and applications of multidisciplinary design optimization in UAV development. The study discusses the integration of aerodynamic analysis, structural optimization, propulsion system selection, weight estimation, stability and controllability assessment, and mission performance evaluation within a comprehensive design framework. In addition, recent developments in computational optimization, numerical simulation, artificial intelligence, and digital engineering are reviewed to demonstrate their contribution to improving UAV efficiency, reliability, and operational capability. The findings indicate that MDO significantly enhances design quality, reduces development time and cost, and enables engineers to develop high-performance UAVs that satisfy increasingly demanding mission requirements. The presented review provides a comprehensive overview of current MDO methodologies and identifies future research directions for next-generation UAV design.