On Switched Event-triggered Full State-constrained Formation Control for Multi-vehicle Systems

TL;DR

This paper introduces a switched event-triggered control framework for multi-vehicle formation systems that handles state constraints, employs neural networks for unknown dynamics, and reduces communication load while ensuring stability.

Contribution

It develops a novel control approach combining nonlinear transformation, neural network approximation, and event-triggered mechanisms for constrained vehicle formation control.

Findings

Achieves stable platoon formation under state constraints.

Reduces communication updates during steady-state.

Ensures bounded signals and excludes Zeno behavior.

Abstract

Vehicular formation control is an important component of intelligent transportation systems (ITSs). In practical implementations, the controller design needs to satisfy multiple state constraints, including inter-vehicle spacing and vehicle speed. When system states approach the constraint boundaries, control singularity and excessive control effort may arise, which limits the practical applicability of existing methods. To address this problem, this paper investigates a class of nonlinear vehicular formation systems for autonomous vehicles (AVs) with uncertain dynamics and develops a switched event-triggered control framework. A smooth nonlinear mapping is first introduced to transform the constrained state space into an unconstrained one, thereby avoiding singularity near the constraint boundaries. A radial basis function neural network (RBFNN) is then employed to approximate the unknown nonlinear dynamics online, based on which an adaptive controller is constructed via the backstepping technique. In addition, a switched event-triggered mechanism (SETM) is designed to increase the control update frequency during the transient stage and reduce the communication burden during the steady-state stage. Lyapunov-based analysis proves that all signals in the closed-loop system remain uniformly bounded and that Zeno behavior is excluded. Simulation results verify that the proposed method achieves stable platoon formation under prescribed state constraints while significantly reducing communication updates.