Evaluation of a pattern matching method for the Tennessee Eastman challenge process

Abstract In this paper, we evaluate multivariate pattern matching methods for the Tennessee Eastman (TE) challenge process. The pattern matching methodology includes principal component analysis based similarity factors and dissimilarity factor of Kano et al., that compare current and historical data. In our similarity factor approach, the start and end times of disturbances are not known a priori and the data are compared by moving a window though the historical data. Comparisons with methods used in earlier case studies of the TE challenge process show advantages of using the proposed similarity factor approach.

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