Robustness and stability are both important properties of a system or model, but they have different concepts and meanings.
Robustness generally refers to how a system or model behaves in the face of various uncertainties, interferences, or noise. A robust system or model can resist these uncertainties and disturbances within a certain range, maintaining the stability of its performance and output. Robustness is concerned with the adaptability and reliability of the system under different conditions.
Stability refers to the stability and convergence of a system or model under specific conditions. Stability is concerned with whether a system is able to return to a stable state or remain within a stable range when disturbed or initial conditions change. Stability is an important prerequisite for the normal operation and reliable operation of the system.
In simple terms, robustness emphasizes the adaptability and reliability of the system under different environments and conditions, while stability focuses on the stability and convergence of the system under specific conditions. Robustness and stability are both important factors to consider in system design and evaluation, and they are interrelated but different.
In practical applications, depending on the specific needs and characteristics of the problem, robustness or stability can be emphasized, or the combined performance of both can be considered.