Output Feedback Sliding Mode Control for Nonlinear Vehicle Platoon Tracking with Multiplication Measurement Errors

Abstract

This paper investigates the nonlinear vehicle platoon tracking problems with multiplicative measurement errors. An output feedback sliding mode based platoon controller is proposed such that the vehicles can asymptotically converge to the desired platoon. To deal with the multiplicative measurement errors and the nonlinear terms of vehicle, a novel radial basis function neural network (RBFNN) based state observer is developed to estimate the relative vehicle states, in which only the vehicle positions are applied into this observer. Then, an output feedback sliding mode based platoon controller is proposed for these nonlinear vehicles. The stability and string stability of this platoon are both strictly analyzed. In final, numerical simulations are presented to illustrate the effectiveness of proposed approaches.