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  • Performance Monitoring of Iterative Learning Control and Development of Generalized Predictive Control for Batch Processes
  • Farasat, Ehsan
  • English
  • batch processes
    iterative learning control
    generalized predictive control
    performance assessment
    two-dimensional identification
  • Jan 30, 2012 10:18 AM
  • Thesis
  • English
  • Adobe PDF
  • 625019 bytes
  • Unlike continuous processes, a batch process has a certain period of operation time, and there are a number of batches in a typical operation. Hence variables in a batch process have dynamics in two dimensions, along time and across batches. Besides, batch processes involve large transient phases covering a wide range of operating envelopes, which cause challenges in both modeling and control. To meet the control objectives of batch processes, set-point tracking and disturbance rejection, iterative learning control (ILC) has been widely attempted. This thesis is concerned with the optimal design and performance assessment of ILC based on the minimum variance benchmark. When performance of ILC is unsatisfactory, alternative control strategies should be considered. Generalized predictive control (GPC) is a popular control strategy for continuous processes. Developing a two-dimensional GPC structure for batch processes is another focus of this research. Finally, ILC and suggested GPC are compared through simulation studies.
  • Master's
  • Master of Science
  • Department of Chemical and Materials Engineering
  • Process Control
  • Spring 2012
  • Huang, Biao (Chemical and Materials Engineering)
  • Huang, Biao (Chemical and Materials Engineering)
    Prasad, Vinay (Chemical and Materials Engineering)
    Tavakoli, Mahdi (Electrical and Computer Engineering)

Apr 24, 2014 5:48 PM


Jan 30, 2012 10:18 AM


Kim Punko