INVESTIGADORES
GONZALEZ Alejandro Hernan
congresos y reuniones científicas
Título:
Geometric properties of kernel partial least squares for non-linear process monitoring
Autor/es:
GODOY, JOSÉ LUIS; BUSTOS, GERMÁN ANDRÉS; GONZÁLEZ, ALEJANDRO HERNÁN; MARCHETTI, JACINTO LUIS
Lugar:
Roma
Reunión:
Congreso; The 5th International Conference on Integrated Modeling and Analysis in Applied Control and Automation (IMAACA 2011); 2011
Resumen:
This work proposes a new strategy for monitoring nonlinear
processes based on Kernel Partial Least Squares
(KPLS). When strongly non-linear process are
considered, a PLS regression model could not be
enough accurate. So, the first stage of the proposed
method is to map the input data to a high-dimension
space, where a linear regression model can be obtained.
Then, an implicit linear regression model relating the
high-dimension space with output space (output data) is
obtained. This model implicitly induces a
decomposition of the high-dimension space into the
Model subspace and the complementary Residual
subspace, being the vectors in the first subspace the
effective domain of the linear regression model. Finally,
once the space decomposition is understood, new
statistics (metrics) for each subspace are proposed to
monitor the process and detect possible abnormal
behaviours. The effectiveness of the method is tested by
means of a synthetic simulation example from the
literature.implicit linear regression model relating the
high-dimension space with output space (output data) is
obtained. This model implicitly induces a
decomposition of the high-dimension space into the
Model subspace and the complementary Residual
subspace, being the vectors in the first subspace the
effective domain of the linear regression model. Finally,
once the space decomposition is understood, new
statistics (metrics) for each subspace are proposed to
monitor the process and detect possible abnormal
behaviours. The effectiveness of the method is tested by
means of a synthetic simulation example from the
literature.