عنوان البحث | ملخص البحث | Research Abstract |
Efficient recursive principal component analysis algorithms for process monitoring | | |
Recursive fault detection and isolation approaches of time-varying processes | | |
Fault diagnosis of time-varying processes using modified reconstruction-based contributions | | |
Model-based fault diagnosis via parameter estimation using knowledge base and fuzzy logic approach | | |
Echo state neural network based state feedback control for SISO afine nonlinear systems | | |
Fault detection of nonlinear processes using fuzzy c-means-based kernel PCA | | |
Observer-based echo-state neural network control for a class of nonlinear systems | | |
Direct adaptive control based on LS-SVM inverse model for nonlinear systems | | |
Simultaneous Fault Detection and Diagnosis Using Adaptive Principal Component Analysis and Multivariate Contribution Analysis | | |
Fault Detection and Isolation Indices for Large-Scale Systems | | |
Residual Signal-based Process Monitoring of Industrial Systems | | |
On-line Fault Detection and Diagnosis of Continuous Processes Based on Mahalanobis Distance | | |
Recursive Partial Decomposition Contributions-based Fault Isolation | | |
Recursive Diagonal Contributions Method for Time Varying Chemical Processes Monitoring | | |
Advanced Principal Component Analysis for process monitoring: A Benchmark Study | | |
Qualitative Model-Based Fault Diagnosis Using Fuzzy Logic | | |