Robust identification of process models from plant data


Abstract:

A precursor to any advanced control solution is the step of obtaining an accurate model of the process. Suitable models can be obtained from phenomenological reasoning, analysis of plant data or a combination of both. Here, we will focus on the problem of estimating (or calibrating) models from plant data. A key goal is to achieve robust identification. By robust we mean that small errors in the hypotheses should lead to small errors in the estimated models. We argue that, in some circumstances, it is essential that special precautions be taken to ensure that robustness is preserved. We present several practical case studies to illustrate the results.

Año de publicación:

2007

Keywords:

  • Closed Loop Identification
  • Robust identification

Fuente:

scopusscopus

Tipo de documento:

Other

Estado:

Acceso restringido

Áreas de conocimiento:

  • Planta
  • Ingeniería de sistemas
  • Automatización

Áreas temáticas de Dewey:

  • Ingeniería química
  • Fabricación
  • Física aplicada
Procesado con IAProcesado con IA

Objetivos de Desarrollo Sostenible:

  • ODS 12: Producción y consumo responsables
  • ODS 15: Vida de ecosistemas terrestres
  • ODS 2: Hambre cero
Procesado con IAProcesado con IA