The Unmanned Vehicular Platoon Control with Quantitative Mismatch
Due to network bandwidth limitations,the control signal may experience losses during trans-mission,which can affect the reliability of the system.To solve this problem,quantization control is in-troduced to convert continuous control signals into discrete control signals.Due to the small transmission bandwidth required for discrete signals,this undoubtedly greatly improves communication efficiency,ef-fectively enhancing the reliability and accuracy of the control system.However,most current research re-sults are based on equal encoding/decoding parameters,without considering possible mismatches in quantization parameters in practice.This article proposes an unmanned vehicular platoon control method with quantitative mismatch to address issues such as input quantization parameter mismatches,external interference,and model uncertainty in unmanned vehicle formation systems.Firstly,a nonlinear dynamic model with input quantization,external interference,and model uncertainty is established.Then,a neu-ral network is used to approximate the nonlinear functions in the model,and an adaptive method is used to estimate the weights,approximation error,quantization error,and external interference of the neural network online.Finally,using Lyapunov stability theory,it is proved that all signals in the closed-loop system are uniformly ultimately bounded,and verify the effectiveness of the proposed scheme through sim-ulation.
万方数据
维普
