Abstract

This paper investigates the vehicle platoon control problems with both velocity constraints and input saturation. Firstly, radial basis function neural networks (RBF NNs) are employed to approximate the unknown driving resistance of a vehicle’s dynamic model. Then, a bidirectional topology, where vehicles can only communicate with their direct preceding and following neighbors, is used to depict the relationship among the vehicles in the platoon. On this basis, a neural adaptive sliding-mode control algorithm with an anti-windup compensation technique is proposed to maintain the vehicle platoon with desired distance. Moreover, the string stability and the strong string stability of the whole vehicle platoon are proven through the stability theorem. Finally, numerical simulations verify the feasibility and effectiveness of the proposed control method.

Highlights

  • The vehicle platoon, which means that all vehicles in a group communicate with each other and regulate their motion to reach the desired intervehicle distance, has received considerable attention in recent years [1, 2]

  • This paper investigates the vehicle platoon control problems with both velocity constraints and input saturation

  • Many other topics on the vehicle platoon control have been discussed in terms of the range policy [8, 9], the communication topology [10,11,12], and the dynamic heterogeneity [13]

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Summary

Introduction

The vehicle platoon, which means that all vehicles in a group communicate with each other and regulate their motion to reach the desired intervehicle distance, has received considerable attention in recent years [1, 2]. Vehicle platoon control can be traced back to the PATH (Partners for Advanced Transit and Highways) program in the 1980s, in which many well-known issues are studied, such as control architecture, collision avoidance, and string stability [5,6,7]. Many other topics on the vehicle platoon control have been discussed in terms of the range policy [8, 9], the communication topology [10,11,12], and the dynamic heterogeneity [13]. Some advanced platoon control algorithms have been proposed for the vehicle dynamics model under the framework of multiagent consensus control [3, 4] and the framework of sliding-mode control [14, 15]. Most of them do not consider the realistic problems in terms of input saturation, velocity constraints, and model nonlinearities

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