Linear quadratic control and estimation synthesis for multi-agent systems with application to formation flight

Abstract

This paper concerns the optimality problem of distributed linear quadratic control in a linear stochastic multi-agent system (MAS). The main challenge stems from MAS network topology that limits access to information from non-neighbouring agents, imposing structural constraints on the control input space. A distributed control-estimation synthesis is proposed which circumvents this issue by integrating distributed estimation for each agent into distributed control law. Based on the agents' state estimate information, the distributed control law allows each agent to interact with non-neighbouring agents, thereby relaxing the structural constraint. Then, the primal optimal distributed control problem is recast to the joint distributed control-estimation problem whose solution can be obtained through the iterative optimization procedure. The stability of the proposed method is verified and the practical effectiveness is supported by numerical simulations and real-world experiments with multi-quadrotor formation flight.