Fast-response voltage regulation is essential for data-center VRMs powering AI workloads, which exhibit both small-amplitude fluctuations and abrupt full-load steps. This paper introduces a control scheme that smoothly integrates the linear controller and nonlinear controller for variable-frequency Series-Capacitor Buck (SCB) converters. First, an accurate small-signal model is derived via a Switching-Synchronized Sampled State-Space (5S) framework, yielding discrete-time transfer functions and root-locus insights for direct digital design. A critical concern for SCB converters is series-capacitor oscillation during heavy load steps if the strict switching sequence is not maintained. To accelerate large-signal transients, a time-optimal control strategy based on Pontryagin’s Maximum Principle relaxes the switching constraints to compute time-optimal switching sequences. A smooth transition logic is proposed that can hand control between the high-bandwidth small-signal controller and the large-signal controller. Lastly, simulations demonstrate sub-microsecond large-signal load-step recovery, over ten times faster than a linear-controller-only design. Preliminary hardware tests indicate a stable rejection to heavy load disturbances with zero steady-state error.