A Novel Multi-Agent Model-Free Adaptive Control Algorithm for a Class of Multivehicle Systems with Constraints

Abstract

To solve the problem of longitudinal cooperative formation driving control of multiple vehicles, a model-free adaptive control algorithm with constraints (cMFAC) is proposed in this paper. In the cMFAC algorithm, a dynamic linearization technique with a time-varying parameter pseudo-gradient (PG) is used to linearize the multivehicle collaborative system. Then, a cMFAC controller is designed. The algorithm sets the input and output constraints at the same time to prevent the vehicle speed and other parameters from exceeding the specified range. The main advantage of the cMFAC algorithm is that the entire control process only needs the input and output data of each vehicle and can effectively handle the input and output constraints. In addition, the stability of the cMFAC method is verified through strict mathematical analysis, and its effectiveness is verified with semi-physical experiments based on a MATLAB/Simulink module and CarSim platform connection environment. It is worth noting that the proposed cMFAC controller is symmetric because the input cost function and PG cost function have symmetric and similar structures, and the forms of the two cost functions are the same.