Coalitional Distributed Model Predictive Control Strategy for Vehicle Platooning Applications

Abstract

This work aims at developing and testing a novel Coalitional Distributed Model Predictive Control (C-DMPC) strategy suitable for vehicle platooning applications. The stability of the algorithm is ensured via the terminal constraint region formulation, with robust positively invariant sets. To ensure a greater flexibility, in the initialization part of the method, an invariant table set is created containing several invariant sets computed for different constraints values. The algorithm was tested in simulation, using both homogeneous and heterogeneous initial conditions for a platoon with four homogeneous vehicles, using a predecessor-following, uni-directionally communication topology. The simulation results show that the coalitions between vehicles are formed in the beginning of the experiment, when the local feasibility of each vehicle is lost. These findings successfully prove the usefulness of the proposed coalitional DMPC method in a vehicle platooning application, and illustrate the robustness of the algorithm, when tested in different initial conditions.

Coalitional Distributed Model Predictive Control Strategy with Switching Topologies for Multi-Agent Systems

“…A DMPC-based coalitional control strategy is developed, in which the reconfiguration of the communication network is jointly decided depending on local string stability criteria. This is different from the DMPC algorithm in [30], where the network topology changes by inserting or removing certain agents, or the robust, min-max DMPC algorithm in [27,28], in which the coalitions are formed when the local feasibility of the optimization problem is lost due to the fact that a terminal constraint is not fulfilled.…”

“…The most recent results by the authors obtained in the coalitional control domain can be classified depending on the methodology used to control the MAS, as follows: (i) coalitional control based on an optimal feedback gain matrix [26], in which each communication topology is described by a different optimal feedback gain matrix, with non-zero elements corresponding to active communication links, and (ii) coalitional control based on a robust DMPC framework [27,28] with a robust, min-max DMPC algorithm, in which the coalitions between agents are formed when the local feasibility with respect to a robust positive invariant terminal set constraint is lost. Furthermore, in [29], a comparative assessment is performed on a vehicle platooning application by evaluating the results achieved using a DMPC strategy and a coalitional control algorithm, formulated using an optimal feedback gain matrix.…”

Coalitional Control Strategy for a Heterogeneous Platoon Application

“…Thus, local interconnected sub-systems are grouped into clusters or coalitions, in order to share information through the communication network, only when necessary from the control objective point of view [19]. In [20], a coalitional DMPC methodology for vehicle platooning applications is presented. The main idea is to introduce the usage of a flexible communication network within the platoon.…”