ThisDisturbance rejection chapterUncertainty attenuation introduces a proactiveProactive, model-based control strategy for robust disturbance rejectionDisturbance rejection and uncertainty attenuationUncertainty attenuation in complex mass–stiffness–damping systemsMass–stiffness–damping system (MKC systemsMKC system). While earlier approaches employed passive integral compensation to address steady-state errors, this chapter presents an active framework that leverages disturbance observationDisturbance observation and feedforward compensationFeedforward compensation. By estimating disturbances from available system signals and preemptively counteracting their effects, the introduced method significantly improves both transient and steady-state performanceSteady-state performance. The chapter presents two enhanced control algorithms, buildingBuilding upon the pre-compensating schemes from Chap.  6 . These new algorithms integrate disturbance estimates into the forward pathForward path, effectively canceling unknown or varying external forcesExternal force before they affect system behavior. The result is a dramatic increase in tracking precision and robustness under real-world conditions, such as payload variations or impulse disturbances. Through simulations, experiments, and comparative analyses, the performance of the introduced disturbance-rejection strategies is validated against traditional approaches. The findings reveal substantial reductions in tracking errors and control effort, even with unmodeled dynamics and sensor noiseSensor noise. Ultimately, this chapter demonstrates that embedding disturbance observationDisturbance observation and compensation within model-based control loops is essential for high-performance, reliable operation in practical electromechanical systemsElectromechanical system.