Journal Papers

Cooperative path following of constrained autonomous vehicles with model predictive control and event‐triggered communications

Nguyen Tuan Hung | António Pascoal | Tor A. Johansen
Abstract:
We present a solution to the problem of multiple vehicle cooperative path fol-lowing (CPF) that takes explicitly into account vehicle input constraints, thetopology of the intervehicle communication network, and time-varying commu-nication delays. The objective is to steer a group of vehicles along given spatialpaths, at speeds that may be path dependent, while holding a feasible geomet-ric formation. The solution involves decoupling the original CPF problem intotwo subproblems: (i) single path following of input-constrained vehicles and (ii)coordination of an input-constrained multiagent system. The first is solved byadopting a sampled-data model predictive control scheme, whereas the latter istackled using a novel distributed control law with an event-triggered communi-cation (ETC) mechanism. The proposed strategy yields a closed-loop CPF systemthat is input-to-state-stable with respect to the system’s state (consisting of thepath following error of all vehicles and their coordination errors) and the sys-tem’s input, which includes triggering thresholds for ETC communications andcommunication delays. Furthermore, with the proposed ETC mechanism, thenumber of communications among the vehicles are significantly reduced. Sim-ulation examples of multiple autonomous vehicles executing CPF maneuvers in2D under different communication scenarios illustrate the efficacy of the CPFstrategy proposed.
Impact factor:
URL:
https://doi.org/10.1002/rnc.4896

Internacional Journal of Robust and Nonlinear Control, Volume 30, pages 2644-2670