Biologically Inspired Control Of A Fleet Of Uavs With Threat Evasion Strategy

Abstract

In this paper, navigation algorithms for a fleet of multiple nonholonomic UAVs capable of evading a chasing predator and also pursuing a desired target are proposed. The proposed biologically-inspired navigation algorithms are used to define path planning trajectories which are tracked by a designed backstepping tracking controller. We implement the group of nonholonomic UAVs in an adaptive network, specifically inspired by the relationship between a school of fish and a predator. This approach approximately simulates an air combat field. To put this in context, the aim is to use a biologically inspired algorithm along with a designed controller to achieve both target pursuance and effective evasion from a predator. This is equivalent to having multiple UAVs on the same mission of attacking a target, while also aware of a predator on pursuit. The UAVs aim to maneuver and evade the predator while also coordinating their movement and behaviors in a cooperative and coherent manner.

Biologically Based Control of a Fleet of Unmanned Aerial Vehicles Facing Multiple Threats

“…2) The work is a direct extension of [43]: The context of this study includes three actors: a target, multiple threats, and a fleet of UAVs. Unlike [43], each actor possesses some cognitive skills and abilities.…”

“…2) The work is a direct extension of [43]: The context of this study includes three actors: a target, multiple threats, and a fleet of UAVs. Unlike [43], each actor possesses some cognitive skills and abilities. The fleet of multiagent UAVs can evade, move in a particular formation toward the target, and in the face of a close incoming threat, evade following a planned path.…”

“…There are several ways to design evasion trajectories. In [43], four quadrants were used to compute the inverse tangent of the angles.…”

“…The use of biologically inspired control of nonholonomic systems under a single threat has been proposed in [43]. A control law based on backstepping control can introduce system oscillations, and a careful selection of the gains is required.…”

Robust non‐fragile approach to resilient design of PID‐based blade pitch control for wind energy conversion system

“…For this purpose, four various performance indices are used such as Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Absolute Error (ITAE), and Integral Time Square Error (ITSE). In this study, the commonly used optimization techniques in engineering optimization applications are considered such as Zeigler Nicolas (ZN), Simplex Algorithm (SA), Genetic Algorithm (GA), and Artificial Bee Colony (ABC) .…”