Data-Driven Fault Diagnosis in Chemical Reactors Using Takagi–Sugeno Models and Zonotopic PI Observers
This paper addresses fault diagnosis in nonlinear systems where reliable mathematical models are unavailable and only input–output measurements are accessible. The proposed methodology consists of three stages. First, a data-driven identification stage is performed using an Adaptive Neuro-Fuzzy Inference System (ANFIS)...