Velocity Tracking for Autonomous Railway-based Urbanloop Pods by Contraction

Overview & Synopsis

We present a model-based methodology to synthesize velocity controllers for individual Urbanloop pods, which are autonomous railway-based vehicles. They are designed for energy-efficient, low-cost, rapid, and seamless urban transport. First, we derive a physics-based pod dynamical model and rigorously reveal that it exhibits two time scales. We then leverage singular perturbation methods combined with recent contraction theory tools to design the controller, guaranteeing that the pod velocity tracks the given reference velocity profile. This controller combines a contractive output-feedback component with a reference-inducing feedforward term. We prove that the trajectories of the original, full-order model exponentially converge to the reference trajectory up to an error proportional to the time-scale separation parameter. Finally, numerical simulations illustrate the relevance of the approach.