Dynamic version of steady state optimizing control of a distillation column by trial method

  • Authors:

  • Y. Sawaragi;T. Takamatsu;K. Fukunaga;E. Nakanishi;H. Tamura

  • Affiliations:

  • Department of Applied Mathematics and Physics, Kyoto University, Kyoto, Japan;Department of Chemical Engineering, Kyoto University, Kyoto, Japan;School of Electrical Engineering, Purdue University, Lafayette, Indiana 47907, U.S.A.;Department of Chemical Engineering, Kobe University, Kobe, Japan;Central Research Laboratory, Mitsubishi Electric Corporation, Amagasaki, Japan

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 1971

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Abstract

The best optimizing control procedure using an automatic optimizing controller, based on a simple pattern-search type, steepest ascent method is presented for a distillation column. The control system is composed of a conventional feedback loop by which the composition of overhead product is maintained constant, and an optimizing control unit which holds the partial derivatives of the objective function with respect to control variables to zero. The objective function used in this study is the profit rate obtained from the distillation process, and the two control variables; feed flow rate and energy supplied to the plant, are used. The computational considerations have been made by simulating the optimizing control system of the distillation column on the Block Diagram Simulator for IBM 7090 in order to ascertain the experimental results. It has been found from the computational considerations that the optimizing speed can be improved by using the trial process during the transient states of the plant. The effect of the sampling period and the step width of control variables on the optimizing speed, optimizing accuracy and stability has been also studied. By decreasing the sampling period optimizing speed would be improved, but the optimizing accuracy would become worse. If the sampling period is too short, the optimization process would become unstable. Concerned with the step width, there might exist best step width for a given sampling period from the view point of optimizing speed, but the optimizing accuracy would become worse by increasing the step width.