제어로봇시스템학회:학술대회논문집
- 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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- Pages.1204-1209
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- 1990
Regression analysis and recursive identification of the regression model with unknown operational parameter variables, and its application to sequential design
- Huang, Zhaoqing (Institute of Chemical Engineering, South China Univ. of Technology) ;
- Yang, Shiqiong (Institute of Chemical Engineering, South China Univ. of Technology) ;
- Sagara, Setsuo (Department of Electrical Engineering, Faculty of Engineering Kyushu University)
- 발행 : 1990.10.01
초록
This paper offers the theory and method for regression analysis of the regression model with operational parameter variables based on the fundamentals of mathematical statistics. Regression coefficients are usually constants related to the problem of regression analysis. This paper considers that regression coefficients are not constants but the functions of some operational parameter variables. This is a kind of method of two-step fitting regression model. The second part of this paper considers the experimental step numbers as recursive variables, the recursive identification with unknown operational parameter variables, which includes two recursive variables, is deduced. Then the optimization and the recursive identification are combined to obtain the sequential experiment optimum design with operational parameter variables. This paper also offers a fast recursive algorithm for a large number of sequential experiments.
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