Abstract This paper investigates the distributed adaptive fault-tolerant control problem for mixed-order connected and autonomous vehicles (CAVs) platoon with actuator faults, saturation, external disturbances, and uncertainties. The studied mixed-order CAVs platoon consists of vehicles with mixed second- and third-order dynamics and all vehicles can have the different numbers and types of states. As the actuator’s efficiency may dynamically fluctuate due to the degrees of wear-outs, aging, and overheating of the actuator during the entire operational process, it is more practical to consider the actuator faults to be nonlinear and time-varying rather than constant. A new adaptive disturbance observer (ADOB) is designed to approximate external disturbances as well as bias faults and improve the control performance of mixed-order CAVs platoon. The Neural networks (NNs)-based adaptive mechanism is designed to approximate uncertainties and actuator efficiency factor, which can mitigate the adverse effects of uncertainties as well as actuator faults and enhance the system’s robustness. For the mixed-order CAVs platoon with actuator faults, actuator saturation, external disturbances, and uncertainties, a novel adaptive fault-tolerant control method based on the developed ADOB and NNs adaptive mechanism is proposed to ensure stability and achieve the control goals of the mixed-order CAVs platoon. The numerical example is provided to demonstrate the effectiveness and advantage of the developed control method.
Yang et al. (Tue,) studied this question.