Active Quantizer-Based Model-Free Adaptive Consensus Tracking for Multiple HSTs Against Sensor Bias

To enhance traffic efficiency and operational safety of multiple high-speed trains (MHSTs) running on the same track, train-to-train (T2T)-based coordination among train groups has become necessary means. In this article, an active quantizer-based model-free adaptive control (AQMFAC) approach is proposed for MHSTs that accounts for random sensor bias in output channels. Firstly, the design process includes the equivalent linearization of train model, the quantizer establishment, and the controller design. Subsequently, theoretical analysis demonstrates that the proposed AQMFAC can converge speed tracking error to a bounded range. Finally, the AQMFAC scheme is validated using a real-time StarSim hardware-in-the-loop (HIL) semi-physical test platform.