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This chapter presentsStructural property a comprehensive analysis of the structural propertiesStructural property ofModel-Following Control (MFC) model-following control (MFC)Enhanced Model-Following Control (enhanced MFC) schemes, with a focus on their role in enhancing robustness against modeling uncertaintiesModeling uncertainty and external disturbances. BuildingBuilding on the uncertainty reduction strategies introduced earlier, the chapter investigates how different MFCEnhanced Model-Following Control (enhanced MFC) configurations—namely outer-loop and inner-loop structures—affect the performance, stability, and sensitivity of mass–stiffness–damping systemsMass–stiffness–damping system (MKC systemsMKC system) and similar dynamic models. Through detailed theoretical derivations and comparative studies, it is shown that the structural placement of the model-following (MF) compensatorModel-following (MF) compensator) critically influences the ability of the system to suppress disturbances and mitigate model mismatches. Specifically, the inner-loop model-followingInner-loop model-following configuration exhibits superior robustness by embedding the compensatory dynamics within the primary control loop, yielding improved sensitivity characteristics and zero steady-state error even under significant perturbations. Equivalence conditions are also explored, revealing how carefully designed weighting functionsWeighting function can render both configurations input–output equivalent, offering design flexibility based on implementation needs. Numerical simulationsNumerical simulation and analytical results confirm the structural advantages of the inner-loop scheme, particularly in frequency-domain robustness and disturbance attenuationDisturbance attenuation. Overall, this chapter establishes a foundational understanding of MFCEnhanced Model-Following Control (enhanced MFC) structure-performance relationships, guiding control engineers in selecting optimal configurations for robust, high-performance control across a wide range of uncertain dynamic systems.

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Structural Properties of Model-Following Schemes

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  • 发表日期：

    2026年

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  • Hai-An Zhu

摘要

This chapter presentsStructural property a comprehensive analysis of the structural propertiesStructural property ofModel-Following Control (MFC) model-following control (MFC)Enhanced Model-Following Control (enhanced MFC) schemes, with a focus on their role in enhancing robustness against modeling uncertaintiesModeling uncertainty and external disturbances. BuildingBuilding on the uncertainty reduction strategies introduced earlier, the chapter investigates how different MFCEnhanced Model-Following Control (enhanced MFC) configurations—namely outer-loop and inner-loop structures—affect the performance, stability, and sensitivity of mass–stiffness–damping systemsMass–stiffness–damping system (MKC systemsMKC system) and similar dynamic models. Through detailed theoretical derivations and comparative studies, it is shown that the structural placement of the model-following (MF) compensatorModel-following (MF) compensator) critically influences the ability of the system to suppress disturbances and mitigate model mismatches. Specifically, the inner-loop model-followingInner-loop model-following configuration exhibits superior robustness by embedding the compensatory dynamics within the primary control loop, yielding improved sensitivity characteristics and zero steady-state error even under significant perturbations. Equivalence conditions are also explored, revealing how carefully designed weighting functionsWeighting function can render both configurations input–output equivalent, offering design flexibility based on implementation needs. Numerical simulationsNumerical simulation and analytical results confirm the structural advantages of the inner-loop scheme, particularly in frequency-domain robustness and disturbance attenuationDisturbance attenuation. Overall, this chapter establishes a foundational understanding of MFCEnhanced Model-Following Control (enhanced MFC) structure-performance relationships, guiding control engineers in selecting optimal configurations for robust, high-performance control across a wide range of uncertain dynamic systems.