Multi-Model Adaptive Control for CACC Applications
Francisco Navas, Vicente Milanés, Carlos Flores, Fawzi Nashashibi
Abstract
This paper proposes a multi-model adaptive control (MMAC) algorithm based on Youla-Kucera (YK) theory to deal with heterogeneity in cooperative adaptive cruise control (CACC) systems. The main idea of MMAC is to choose the plant in a predefined set that best approximates the system dynamics, applying the corresponding predesigned controller. A set of linear plants describing different vehicle dynamics is defined. Different CACC controllers are designed depending on these linear plants. Simulation and experimental results prove how MMAC determines the closest plant in the set, choosing the CACC system able to ensure string stability.
Topics & Concepts
Cooperative Adaptive Cruise ControlControl theory (sociology)Controller (irrigation)Adaptive controlStability (learning theory)Set (abstract data type)Control engineeringComputer scienceControl (management)Cruise controlEngineeringArtificial intelligenceBiologyAgronomyMachine learningProgramming languageTraffic control and managementTransportation Planning and OptimizationAutonomous Vehicle Technology and Safety