Control of Multi-Agent Collaborative Fixed-Wing UASs in Unstructured Environment

Abstract

Swarms of unmanned aircraft are the inevitable future of the aerospace industry. In recent years, swarming robots and aircraft have been a subject of much interest; however, many research projects make impractical assumptions such as point mass dynamics with no aerodynamic effects for aircraft models, and most works stop short of fully validating their methods via flight testing. This work presents a proximity based guidance, navigation, and control of multi-agent fixed-wing unmanned aerial systems in an unstructured environment. A scalable swarm navigation method is developed using adaptive moving mesh partial differential equations controlled by the free energy heat flow equation. To emulate the physics-based dynamic characteristics of fixed-wing UASs, mesh nodes are constrained by aircraft six degrees of freedom equations of motion. An optimal control based path planning using virtual points was developed and constrained with aircraft dynamical limitations. Lateral acceleration is used for lateral guidance of aircraft and the aircraft pitch attitude error is used for longitudinal guidance of multi-agent unmanned aerial systems. A decentralized optimal automatic controller was developed to control each system. Using an advanced in-house autopilot system, validation and verification flight tests were successfully conducted using two large unmanned aerial systems with four meter wingspans flying at 35 knots.