Formation Scaling Maneuver Control of Multiagent Systems: An Approach Based on Distributed Optimization

This article investigates a method of formation scaling maneuver for second-order multiagent systems. The agents track a reference trajectory in the expected configuration and perform scaling maneuver to optimize a time-varying global cost function. For online calculation of the formation scale that is optimal to the cost function, every agent is assigned a local scaling factor, and a distributed optimizer is proposed so that the local scaling factors are convergent to the consensual optimality of the global cost function. Then, the expected positions are derived based on the kinematics of the formation center, the nominal configuration, and the optimal scaling factor. A tracking controller is subsequently designed so that formation scaling maneuver is performed when the agents track the expected positions. Particularly, the optimizer follows the gradient tracking framework and is improved by adopting the dynamic average consensus and extended state observer techniques. An experiment on a cluster of quadrotor autonomous aerial vehicles is performed to verify the proposed method.