摘要The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focus-ing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper pres-ents an adaptive disturbance rejection balance controller based on a Variable-inertia Centroidal Model Predictive Control(ViC-MPC)approach,designed to address both minor disturbances that affect standing balance and major disturbances requiring stepping adjustments.The controller also facilitates reliable balance recovery after stepping adjustments.The humanoid robot is modeled as a spatial variable-inertia ellipsoid,representing the distribution of centroidal dynamics,with the contact wrenches optimized in real-time through a customized MPC formulation.Inspired by capturability-based constraints,we propose an adaptive dynamic stability transition strategy.This strat-egy is activated based on the Retrospective Horizon Average Centroidal Velocity(RHACV)and the Capture Point(CP),ensuring effective stepping adjustments and disturbance rejection.With the torque-controlled humanoid robot BHR8P,extensive simulation and experimental results demonstrate the effectiveness of the proposed method,high-lighting its capability to adapt to and recover from various disturbances with improved stability.