Edward P. Gatzke، نويسنده , , Francis J. Doyle III، نويسنده ,

1384450

Use of multiple models and qualitative knowledge for on-line moving horizon disturbance estimation and fault diagnosis

11414

An integrated fault detection, fault isolation, and parameter estimation technique is presented in this paper. Process model parameters are treated as disturbances that dynamically affect the process outputs. A moving horizon estimation technique minimizes the error between process and model measurements over a finite horizon by calculating model parameter values across the estimation horizon. To implement qualitative process knowledge, this minimization is constrained such that only a limited number of different faults (parameters) may change during a specific horizon window. Multiple linear models are used to capture nonlinear process characteristics such as asymmetric response, variable dynamics, and changing gains. Problems of solution multiplicity and computational time are addressed. Results from a nonlinear chemical reactor simulation are presented.

339

Multiple linear models , Moving horizon estimation , Mixed integer programming , Disturbance estimation

Studia Iranica

352

352