Cooperative control for multi-vehicle swarms

The cooperative control of large-scale multi-agent systems has gained a significant interest in recent years from the robotics and control communities for multi-vehicle control. One motivator for the growing interest is the application of spatially and temporally distributed multiple unmanned aerial vehicle (UAV) systems for distributed sensing and collaborative operations. In this research, the multi-vehicle control problem is addressed using a decentralised control system. The work aims to provide a decentralised control framework that synthesises the self-organised and coordinated behaviour of natural swarming systems into cooperative UAV systems. The control system design framework is generalised for application into various other multi-agent systems including cellular robotics, ad-hoc communication networks, and modular smart-structures. The approach involves identifying su itable relationships that describe the behaviour of the UAVs within the swarm and the interactions of these behaviours to produce purposeful high-level actions for system operators. A major focus concerning the research involves the development of suitable analytical tools that decomposes the general swarm behaviours to the local vehicle level. The control problem is approached using two-levels of abstraction; the supervisory level, and the local vehicle level. Geometric control techniques based on differential geometry are used at the supervisory level to reduce the control problem to a small set of permutation and size invariant abstract descriptors. The abstract descriptors provide an open-loop optimal state and control trajectory for the collective swarm and are used to describe the intentions of the vehicles. Decentralised optimal control is implemented at the local vehicle level to synthesise self-organised and cooperative behaviour. A deliberative control scheme is implemented at the local vehicle le vel that demonstrates autonomous, cooperative and optimal behaviour whilst the preserving precision and reliability at the local vehicle level

Distributed and cooperative decision making for multi-UAV systems with applications to collaborative electronic warfare

In this paper, a theoretical control framework for distributed cooperative decision making for an ensemble of UAVs is presented. A decentralized optimization problem was proposed for the control of multiple UAVs for cooperative decoy jamming of an ISAR radar system. Each vehicle was treated as a socially capable and intelligent agent that used neighboring information to influence its own behavior and achieve the desired group behavior. The optimization problem was formulated using a linear superposition of individual and group tasks and decentralized using a neighborhood construction. Neighboring vehicles were coupled using the aggregate cost function and consensus protocols. To achieve coordination and consensus a decentralized control scheme based on a decentralized model predictive control strategy was developed and implemented. The decentralized model predictive control algorithm synchronized the input of neighboring vehicles and achieved a consensus in the output at each prediction horizon. The consensus of neighboring vehicles was described by the group task. The algorithm was simulated for an ensemble of small-scale UAVs for decoy jamming. Given a specific radar cross section for each UAV, the UAVs were able to self-organize and coordinate their behavior using the developed algorithm and achieve a collective radar signature comparable to a given aircraft model. Preliminary results also demonstrated optimal and closed-loop stable behavior

Multi-agent formation control of UAVs

A unified theoretical approach to multi-agent formation control of UAVs was presented. Intelligent path planning methods were used to coordinate flock agents into formation patterns. Simulation results demonstrated decentralised and self-organised behaviour. Optimal constraints were applied, and the algorithm was simulated for a flock of UAVs for multi-point engagement operations

Control design for UAV swarming

The collective behaviour observed in many social insects and animals provides the inspiration for the development of multi-vehicle control systems. The distributed nature of the multi-vehicle control problem enhances the performance of the collective system along the dimensions of scalability, robustness, and fault tolerance. The distributed/decentralized nature of the cooperative control task introduces many sub-problems often associated with network control design. In this paper, a survey of recent results in the field of cooperative control for multi-vehicle systems is presented. Various applications are discussed and presented in a mathematical framework to illustrate the major features of the cooperative control problem. Theoretical results for various cooperative control strategies are presented by topic and applied to the multi-vehicle applications