Batch-to-batch iterative optimal control of batch processes based on dynamic quadratic criterion

  • Authors:

  • Li Jia;Jiping Shi;Dashuai Cheng;Luming Cao;Min-Sen Chiu

  • Affiliations:

  • Shanghai Key Laboratory of Power Station Automation Technology, Department of Automation, College of Mechatronics Engineering and Automation, Shanghai University, Shanghai, China;Shanghai Key Laboratory of Power Station Automation Technology, Department of Automation, College of Mechatronics Engineering and Automation, Shanghai University, Shanghai, China;Shanghai Key Laboratory of Power Station Automation Technology, Department of Automation, College of Mechatronics Engineering and Automation, Shanghai University, Shanghai, China;Shanghai Key Laboratory of Power Station Automation Technology, Department of Automation, College of Mechatronics Engineering and Automation, Shanghai University, Shanghai, China;Faculty of Engineering, National University of Singapore, Singapore

  • Venue:
  • LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part I
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

A novel dynamic parameters-based quadratic criterion-iterative learning control is proposed in this paper. Firstly, quadratic criterion-iterative learning control with dynamic parameters is used to improve the performance of iterative learning control. As a result, the proposed method can avoid the problem of initialization of the optimization controller parameters, which are usually resorted to trial and error procedure in the existing iterative algorithms used for the optimization of batch process. Next, we make the first attempt to give rigorous description and proof to verify that a perfect tracking performance can be obtained. Lastly, examples are used to illustrate the performance and applicability of the proposed method.