Observer-based hybrid dynamic event-triggered adaptive neural network control for heterogeneous vehicular platoon...

In this paper, the output-feedback control problem under adaptive neural network (NN) hybrid dynamic event-triggered control (HDETC) for nonlinear heterogeneous vehicular platoon systems (HVPSs) is investigated using extended state observers (ESOs) and high-order feedback filters. NNs are utilized to approximate the lumped uncertainties of HVPSs, and ESOs are adopted to estimate unknown internal states and external disturbances. Then, based on the limited network communication bandwidth and resources, to reduce the data transmission frequency, which encompasses inter-vehicle communication, as well as the intra-vehicle communication within each vehicle including the uplink from sensors and the downlink to actuators, a novel hybrid dynamic event-triggered control (HDETC) communication mechanism is designed. Furthermore, in order to produce smooth output estimates with the required differentiability, high-order feedback filters are developed, thus resolving the non-differentiability problem of virtual control signals in the backstepping control design. By formulating a practical spacing policy and carrying out Lyapunov stability analysis, an adaptive NN-HDETC control scheme is further presented, which can ensure the boundedness of all signals and string stability of the HVPSs. Therefore, both the individual and string stability of HVPSs can be achieved. Finally, simulation analyses are carried out to confirm the efficacy of the developed heterogeneous vehicular platoon control (HVPC) scheme.