Adaptive Neural Control of Connected Vehicular Platoons With Actuator Faults and Constraints
Jiahui Wei, Yan‐Jun Liu, Hao Chen, Lei Liu
Abstract
This paper focuses on the adaptive neural control problem for a connected vehicles platoon system with external disturbances, actuator fault and constraints. Then, the tangent barrier Lyapunov function is introduced into the control design to solve the time-varying position and velocity constraints in a vehicle platoon. Since the selected engine dynamics model is nonlinear, the neural network is adopted to approximate the unknown internal vehicle dynamics. Moreover, the actuator fault effect is addressed by the designed adaptive law designed based on the projection operator. It can be eventually confirmed that all the involved closed-loop signals are bounded based on the Lyapunov stability theory. Finally, a comparative simulation shows the effectiveness of the proposed control scheme.