具有量化不匹配的无人车编队控制  

The Unmanned Vehicular Platoon Control with Quantitative Mismatch

作　　者：李平 蔡晓晰 周明政[1] 高树论 矫健 LI Ping;CAI Xiao-xi;ZHOU Ming-zheng;GAO Shu-lun;JIAO Jian(The 52^(nd) Research Institute of China Electronics Technology Corporation,Hangzhou 311100,China)

机构地区：[1]中国电子科技集团公司第五十二研究所,浙江杭州311100

出　　处：《中国电子科学研究院学报》2024年第3期263-271,共9页Journal of China Academy of Electronics and Information Technology

摘　　要：由于网络带宽的限制,控制信号在传输过程中可能存在损耗,严重时会影响系统的可靠性。为了解决这个问题,通过引入量化控制可以将连续的控制信号转换为离散的控制信号,由于离散信号所需的传输带宽较小,这无疑极大提高了通信效率,有效增强了控制系统的可靠性和精确性。但目前大多数研究成果是基于编码/解码参数相等的,并未考虑实践中可能存在量化参数不匹配问题。文中针对无人车编队系统中存在输入量化参数不匹配、外部干扰及模型不确定性等问题,提出了一种具有量化不匹配的无人车编队控制方法。首先,建立带有输入量化、外部干扰及模型不确定性的非线性动力学模型;然后,利用神经网络近似逼近模型中的非线性函数,自适应方法在线估计神经网络权重、逼近误差、量化误差及外部干扰;最后,通过李雅普诺夫稳定性理论,证明闭环系统所有信号的一致最终有界性,并通过仿真验证所提方法的有效性。Due to network bandwidth limitations,the control signal may experience losses during transmission,which can affect the reliability of the system.To solve this problem,quantization control is introduced 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,effectively enhancing the reliability and accuracy of the control system.However,most current research results 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 neural 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 simulation.

关 键 词：编队控制 量化不匹配 神经网络 自适应方法 队列稳定性 

分 类 号：TN91[电子电信—通信与信息系统] TP273[电子电信—信息与通信工程]