Two stage switching control for autonomous formation flight of unmanned aerial vehicles

Acta Mechanica Et Automatica

2016

Implementations of multi-UAV systems can be divided mainly into two different approaches, centralised system that synchronises positions of each vehicle by a ground station and an autonomous system based on decentralised control, which offers more flexibility and independence. Decentralisation of multi-UAV control entails the need for information sharing between all vehicles, what in some cases could be problematic due to a significant amount of data to be sent over the wireless network. To improve the reliability and the throughput of information sharing inside the formation of UAVs, this paper proposes an approach that combines virtual structure with a leader and two flocking behaviours. Each UAV has assigned different virtual migration point referenced to the leader's position which is simultaneously the origin of a formation reference frame. All migration points create together a virtual rigid structure. Each vehicle uses local behaviours of cohesion and repulsion respectively, to track its own assigned point in the structure and to avoid a collision with the previous UAV in the structure. To calculate parameters of local behaviours, each UAV should know position and attitude of the leader to define the formation reference frame and also the actual position of the previous UAV in the structure. Hence, information sharing can be based on a chain of local peer-to-peer communication between two consecutive vehicles in the structure. In such solution, the information about the leader could be sequentially transmitted from one UAV to another. Numerical simulations were prepared and carried out to verify the effectiveness of the presented approach. Trajectories recorded during those simulations show collective, coherence and collision-free flights of the formation created with five UAVs.

Section: Introductionmentioning

confidence: 99%

Multi-UAV Flight using Virtual Structure Combined with Behavioral Approach

Acta Mechanica Et Automatica

2016

“…1, reference positions of UAVs can be determined by predefined points located in a local coordinate frame L, whose origin is placed at the gravity centre of the leader, and its axes are parallel to the axes of the leader's body. Therefore, coordinates of these points can be expressed by equation (1). In the equation, index i in the subscripts refers to the order of UAVs placed behind and in reference to the leader, identically on its both sides.…”

Section: Formation Flight With Algorithm Of Flexible Structurementioning

confidence: 99%

“…Otherwise, the vehicle cannot determine its own behaviors, especially repulsion or cohesion. The last approach, based on the leader-follower relation, is relatively the simplest one, but as it was proved it requires control switching between position control and the course control to achieve the effective flight (Ambroziak and Gosiewski, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Most of the research in this field is focused on three different approaches, i.e. formation flights based on a rigid virtual structure (Norman and Ambroziak and Gosiewski, 2014). In the first approach, UAVs create a rigid structure, where relative distances between UAVs should be constant during a flight as much as it is possible (Norman and Hugh, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Flexible Structure Control Scheme of a UAVs Formation to Improve the Formation Stability During Maneuvers

Acta Mechanica Et Automatica

Ambroziak

2017

Self Cite

Abstract:One of the issues related to formation flights, which requires to be still discussed, is the stability of formation flight in turns, where the aerodynamic conditions can be substantially different for outer vehicles due to varying bank angles. Therefore, this paper proposes a decentralized control algorithm based on a leader as the reference point for followers, i.e. other UAVs and two flocking behaviors responsible for local position control, i.e. cohesion and repulsion. But opposite to other research in this area, the structure of the formation becomes flexible (structure is being reshaped and bent according to actual turn radius of the leader. During turns the structure is bent basing on concentred circles with different radiuses corresponding to relative locations of vehicles in the structure. Simultaneously, UAVs' airspeeds must be modified according to the length of turn radius to achieve the stability of the structure. The effectiveness of the algorithm is verified by the results of simulated flights of five UAVs.

“…A team of fixed-wing UAVs must be more robust against failures of the agents and of the communication, in order to achieve coherence of the team. The same concerns simpler methods such as the leader-follower approach and its variant, which is based on a two-stage switching control [3].…”

Section: Introductionmentioning

confidence: 99%

Fixed-Wing UAVs Flock Control through Cohesion and Repulsion Behaviours Combined with a Leadership

International Journal of Advanced Robotic Systems

Ołdziej

2016

The aim of this paper is to present a novel approach to swarm control of small fixed-wing UAVs, which combines only two flocking behaviours with a leadership feature. In the presented approach, two fundamental rules of Reynolds flocking are applied, i.e., cohesion and repulsion, as the base of a decentralized control of self-organization of the flock. These rules are combined with a leadership feature, which is responsible for a global behaviour of guidance, as in the case of animals. Such a bio-inspired combination allows the achievement of a coherent collective flight of a flock of fixed-wing UAVs without applying formal behaviours of migration and alignment. This highly simplifies an implementation of the algorithm. The presented results include both numerical simulations and experimental flights, which validate the hardware implementation of the approach.