Data Driven Fault Diagnosis and Fault Tolerant Control: Some Advances and Possible New Directions: Data Driven Fault Diagnosis and Fault Tolerant Control: Some Advances and Possible New Directions
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Hong Wang | Tianyou Chai | Martin Brown | Jin-Liang Ding | T. Chai | Hong Wang | Martin Brown | Jinliang Ding
[1] In-Beum Lee,et al. Multiblock PLS-based localized process diagnosis , 2005 .
[2] H. Wang,et al. Control of conditional output probability density functions for general nonlinear and non-Gaussian dynamic stochastic systems , 2003 .
[3] Julian Morris,et al. On-line monitoring of a sugar crystallization process , 2005, Comput. Chem. Eng..
[4] José C. Menezes,et al. Multivariate monitoring of fermentation processes with non-linear modelling methods , 2004 .
[5] Riccardo Leardi,et al. Industrial experiences with multivariate statistical analysis of batch process data , 2006 .
[6] ChangKyoo Yoo,et al. On-line batch process monitoring using a consecutively updated multiway principal component analysis model , 2003, Comput. Chem. Eng..
[7] S. Joe Qin,et al. Semiconductor manufacturing process control and monitoring: A fab-wide framework , 2006 .
[8] Hong Wang,et al. Optimal probability density function control for NARMAX stochastic systems , 2008, Autom..
[9] Hong Wang,et al. Fault detection and diagnosis for general stochastic systems using B-spline expansions and nonlinear filters , 2005, IEEE Transactions on Circuits and Systems I: Regular Papers.
[10] Fuli Wang,et al. Adaptive Monitoring Based on Independent Component Analysis for Multiphase Batch Processes with Limited Modeling Data , 2008 .
[11] Rolf Isermann,et al. Hierarchical motor diagnosis utilizing structural knowledge and a self-learning neuro-fuzzy scheme , 2000, IEEE Trans. Ind. Electron..
[12] ChangKyoo Yoo,et al. Statistical monitoring of dynamic processes based on dynamic independent component analysis , 2004 .
[13] Ana P Ferreira,et al. Study of the application of multiway multivariate techniques to model data from an industrial fermentation process. , 2007, Analytica chimica acta.
[14] J Glassey,et al. Issues in the development of an industrial bioprocess advisory system. , 2000, Trends in biotechnology.
[15] Hong Wang,et al. Minimum entropy control of closed-loop tracking errors for dynamic stochastic systems , 2003, IEEE Trans. Autom. Control..
[16] Ali Cinar,et al. Intelligent process monitoring by interfacing knowledge-based systems and multivariate statistical monitoring , 2000 .
[17] Yixin Diao,et al. Stable fault-tolerant adaptive fuzzy/neural control for a turbine engine , 2001, IEEE Trans. Control. Syst. Technol..
[18] Manabu Kano,et al. Data-based process monitoring, process control, and quality improvement: Recent developments and applications in steel industry , 2008, Comput. Chem. Eng..
[19] Lei Guo,et al. Minimum entropy filtering for multivariate stochastic systems with non-Gaussian noises , 2005, Proceedings of the 2005, American Control Conference, 2005..
[20] Chunhui Zhao,et al. Adaptive Monitoring Method for Batch Processes Based on Phase Dissimilarity Updating with Limited Modeling Data , 2007 .
[21] Ali Cinar,et al. An intelligent system for multivariate statistical process monitoring and diagnosis. , 2002, ISA transactions.
[22] Manabu Kano,et al. Comparison of statistical process monitoring methods: application to the Eastman challenge problem , 2000 .
[23] ChangKyoo Yoo,et al. On-line monitoring of batch processes using multiway independent component analysis , 2004 .
[24] J. Morris,et al. Monitoring process manufacturing performance , 2002 .
[25] George W. Irwin,et al. Improved reliability in diagnosing faults using multivariate statistics , 2006, Comput. Chem. Eng..
[26] Weihua Li,et al. Recursive PCA for adaptive process monitoring , 1999 .
[27] Christos Georgakis,et al. Disturbance detection and isolation by dynamic principal component analysis , 1995 .
[28] S Albert,et al. Multivariate statistical monitoring of batch processes: an industrial case study of fermentation supervision. , 2001, Trends in biotechnology.
[29] Hong Wang,et al. Actuator fault diagnosis: an adaptive observer-based technique , 1996, IEEE Trans. Autom. Control..
[30] Lei Guo,et al. Observer-Based Optimal Fault Detection and Diagnosis Using Conditional Probability Distributions , 2006, IEEE Transactions on Signal Processing.
[31] Jose A. Romagnoli,et al. An integration mechanism for multivariate knowledge-based fault diagnosis , 2002 .
[32] Manabu Kano,et al. A new multivariate statistical process monitoring method using principal component analysis , 2001 .
[33] Donghua Zhou,et al. Real-time Reliability Prediction for a Dynamic System Based on the Hidden Degradation Process Identification , 2008, IEEE Transactions on Reliability.
[34] Jin Hyun Park,et al. Fault detection and identification of nonlinear processes based on kernel PCA , 2005 .
[35] Hong Wang,et al. On the use of adaptive updating rules for actuator and sensor fault diagnosis , 1997, Autom..
[36] Hong Wang. Minimum entropy control of non-Gaussian dynamic stochastic systems , 2002, IEEE Trans. Autom. Control..
[37] ChangKyoo Yoo,et al. Statistical process monitoring with independent component analysis , 2004 .