Cooperative Constrained Control of Distributed Agents With Nonlinear Dynamics and Delayed Information Exchange: A Stabilizing Receding-Horizon Approach

By Elisa Franco, Lalo Magni, Thomas Parisini, Marios M. Polycarpou, Davide Martino Raimondo. 2008

168 citations recorded by the source corpus.

This paper addresses the problem of cooperative control of a team of distributed agents with decoupled nonlinear discrete-time dynamics, which operate in a common environment and exchange-delayed information between them. Each agent is assumed to evolve in discrete-time, based on locally computed control laws, which are computed by exchanging delayed state information with a subset of neighboring agents. The cooperative control problem is formulated in a receding-horizon framework, where the control laws depend on the local state variables (feedback action) and on delayed information gathered from cooperating neighboring agents (feedforward action). A rigorous stability analysis exploiting the input-to-state stability properties of the receding-horizon local control laws is carried out. The stability of the team of agents is then proved by utilizing small-gain theorem results.

Subfields: Computer Networks and Communications, Control and Systems Engineering, Modeling and Simulation

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Citations in the corpus

An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination (2012, background): “The main research in this topic [ 195]–[197] has been devoted to deriving proper distributed control algorithms for a team of agents such that they can reach some d esire formation by optimizing some finite-horizon cost functions in scenarios with or without t ime delay.”
Architectures for distributed and hierarchical Model Predictive Control - A review (2009, methodology): “In the context of MPC, the coordination of independent nonlinear discrete-time systems with delayed intercommunication has been considered in [29], which also provides stability results obtained by resorting to Input to State Stability (ISS) concepts.”
Distributed Receding Horizon Control of Vehicle Platoons: Stability and String Stability (2012, background): “Distributed receding horizon control of multiple decoupled vehicles has also been explored for linear [13], [18] and nonlinear [7], [9], [11] vehicle dynamics, with coupling in cost functions and/or constraints.”
Distributed model predictive control: A tutorial review and future research directions (2013, unknown): “…situations should be carefully accounted for in the con-trol problem formulation and solution In order to achieve mode transitions in an optimal setting and accommodate input/state constraints, distributed model predictive control (MPC) framework can be employed, particularly in cases where the…”