Titlebook: Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems; Steven X. Ding Book 2014 Springer-Verlag London 2014 Data-driven

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Canonical Variate Analysis Based Process Monitoring and Fault Diagnosisonical correlation analysis (CCA) is a further MVA method, which is also, in particular in the control community, known as canonical variate analysis (CVA) and recognized as a standard method for system identification.

Pageant

Introduction, Preliminaries and I/O Data Set Models domains. Thanks to their intimate relations to automatic control systems, model-based schemes are widely accepted as a powerful technology in dealing with process monitoring and fault diagnosis for dynamic processes.

刺耳

Economics of Justice and Peace in the WorldPrincipal component analysis (PCA) is a basic method of multivariate analysis (MVA) and plays, both in the research and application domains, an important role.

外来

Springer Studies in Alternative EconomicsRoughly speaking, partial least squares (PLS) regression is a multivariate analysis method that constructs a linear regression between two data sets expressed in form of data matrices.

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J. A. Canul-Polanco,O. M. JensenThe key of data-driven fault diagnosis schemes consists in a direct identification of key fault detection statistics like covariance matrices applied in the MVA or SIM based methods.

亲密

IMP: A Simple Imperative LanguageIn the previous chapter, we have introduced the fault-tolerant architecture and the associated design parameters. In this chapter, we focus on the data-driven design of the state feedback gain matrix, an H-PRIO parameter of the fault-tolerant architecture, and its application to the observer-based control schemes.

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Application of Partial Least Squares Regression to Fault DiagnosisRoughly speaking, partial least squares (PLS) regression is a multivariate analysis method that constructs a linear regression between two data sets expressed in form of data matrices.