Realistic disturbance modeling using Hidden Markov Models: Applications in model-based process control

✍ Scribed by Wee Chin Wong; Jay H. Lee

• Publisher: Elsevier Science
• Year: 2009
• Tongue: English
• Weight: 968 KB
• Volume: 19
• Category: Article
• ISSN: 0959-1524
• DOI: 10.1016/j.jprocont.2009.04.014

✦ Synopsis

Understanding and modeling disturbances play a critical part in designing effective advanced modelbased control solutions. Existing linear, stationary disturbance models are oftentimes limiting in the face of time-varying characteristics typically witnessed in process industries. These include intermittent drifts, abrupt changes, temporary oscillations, outliers and the likes. This work proposes a Hidden Markov Model-based framework to deal with such situations that exhibit discrete, modal behavior. The usefulness of the proposed disturbance framework -from modeling to ensuring the integral action under a wide variety of scenarios -is demonstrated through several examples.