English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Papermaking is a large-scale two-dimensional process. It has to be monitored and controlled continuously in order to ensure that the qualities of paper products stay within their specifications. There are two types of control problems involved in papermaking processes: machine directional (MD) control and cross directional (CD) control. Machine direction refers to the direction in which paper sheet travels and cross direction refers to the direction perpendicular to machine direction. The objectives of MD control and CD control are to minimize the variation of the sheet quality measurements in machine direction and cross direction, respectively. This chapter considers the design and applications of model predictive control (MPC) for papermaking MD and CD processes. MPC, also known as moving horizon control (MHC), originated in the late seventies and has developed considerably in the past two decades (Bemporad and Morari 2004; Froisy 1994; Garcia et al. 1998; Morari & Lee 1999; Rawlings 1999; Chu 2006). It can explicitly incorporate the process’ physical constraints in the controller design and formulate the controller design problem into an optimization problem. MPC has become the most widely accepted advanced control scheme in industries. There are over 3000 commercial MPC implementations in different areas, including petro-chemicals, food processing, automotives, aerospace, and pulp and paper (Qin and Badgwell 2000; Qin and Badgwell 2003). Honeywell introduced MPC for MD controls in 1994; this is likely the first time MPC technology was applied to MD controls (Backstrom and Baker, 2008). Increasingly, paper producers are adopting MPC as a standard approach for advanced MD controls. MD control of paper machines requires regulation of a number of quality variables, such as paper dry weight, moisture, ash content, caliper, etc. All of these variables may be coupled to the process manipulated variables (MV’s), including thick stock flow, steam section pressures, filler flow, machine speed, and disturbance variables (DV’s) such as slice lip adjustments, thick stock consistency, broke recycle, and others. Paper machine MD control is truly a multivariable control problem. In addition to regulation of the quality variables during normal operation, a modern advanced control system for a paper machine may be expected to provide dynamic economic optimization on the machine to reduce energy costs and eliminate waste of raw materials. For machines that produce more than one grade of paper, it is desired to have an automatic grade change feature that will create and track controlled variable (CV) and MV

Model Predictive Control and Optimization for Papermaking Processes