Application of a neural network to evaluation of interactions in a MIMO process

Authors

  • Takehiro Ohba,

    1. Research Laboratory of Resources Utilization, Tokyo Institute of Technology, Yokohama 226, Japan
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  • Masaru Ishida

    Corresponding author
    1. Research Laboratory of Resources Utilization, Tokyo Institute of Technology, Yokohama 226, Japan
    • Research Laboratory of Resources Utilization, Tokyo Institute of Technology, Yokohama 226, Japan
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Abstract

A neural-net controller for multivariable systems is presented. The neural network for this controller has a structure in which small neural-net controllers for SISO systems are assembled and offers a unique path from the controlled variable to the manipulated variable. By using such a structured assembly, the interactions among the controlled and manipulated variables can be evaluated. The simulation results for both a linear three-input and three-output system and a crystal-growth process indicate that the proposed controller has the ability to learn the interactions between the control variables and to disclose the features of the interactions.

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