MNL58

    Modern Computer Process Control Refining Units

    Published: Jan 2013

      Format Pages Price  
    PDF Version (816K) 18 $25   ADD TO CART
    Complete Source PDF (98M) 18 $260   ADD TO CART


    Abstract

    Advanced process control (APC) applications have become a norm for refining and petrochemical units. Evolving along the path of regulatory control to advanced regulatory control (ARC) to conventional APC to multivariable predictive control (MVPC), MVPC technology has not only been well established and proven but also has become the main workhorse of refinery process control and optimization, with several thousand applications implemented in the last 30 years. Recent additions of neural networks technology for inferential predictions, advisory/expert systems for abnormal situation management, and fuzzy logic for combining operating heuristics and rules with mathematical control have increased the control technology arsenal to monitor, control, and optimize during the normal operating period and during periods of fast ramping, feed changes, and unplanned events. This chapter provides the basis of understanding the various control technologies and their integration to meet the safety, operational, and economic objectives of refinery APC applications. The intention is not to provide academic theory of control, but to provide sufficient base knowledge and practical configuration examples of what has actually worked in real-life applications. Cheat-sheet-type configuration for MVPC control and a list of common conventional APC applications required to automate each unit are presented for most of the major refining units.

    Keywords:

    Advisory systems, catalytic reformer unit control, control linearity, control superposition, crude unit control, delayed coker control, expert systems, fluidized catalyst cracker unit control, fuzzy logic control, gas plant unit control, hydrocracker unit control, inferential predictions, multivariable predictive control, neural-networks-based inferential predictions, vacuum unit control


    Author Information:

    Jaisinghani, Ravi
    Intelligent Optimization Group, Inc., Houston, TX


    Paper ID: MNL5820131212715

    Committee/Subcommittee: D02.04

    DOI: 10.1520/MNL5820131212715


    CrossRef ASTM International is a member of CrossRef.

    ISBN10:
    ISBN13: 978-0-8031-7022-3