| A novel dynamic PCA algorithm for dynamic data modeling and process monitoring |
53 |
| Prediction model of end-point phosphorus content in BOF steelmaking process based on PCA and BP neural network |
22 |
| Statistical process monitoring as a big data analytics tool for smart manufacturing |
21 |
| Distributed predictive modeling framework for prediction and diagnosis of key performance index in plant-wide processes |
21 |
| Optimal PI and PID control of first-order plus delay processes and evaluation of the original and improved SIMC rules |
20 |
| Annulus-event-based fault detection, isolation and estimation for multirate time-varying systems: Applications to a three-tank system |
18 |
| Automated feature learning for nonlinear process monitoring - An approach using stacked denoising autoencoder and k-nearest neighbor rule |
17 |
| Review of control strategies for improving the energy flexibility provided by heat pump systems in buildings |
16 |
| Online reduced kernel principal component analysis for process monitoring |
16 |
| Big data quality prediction in the process industry: A distributed parallel modeling framework |
16 |
| Real-time fault detection and diagnosis using sparse principal component analysis |
15 |
| Semisupervised learning for probabilistic partial least squares regression model and soft sensor application |
14 |
| Dynamic concurrent kernel CCA for strip-thickness relevant fault diagnosis of continuous annealing processes |
13 |
| A data-driven robust optimization approach to scenario-based stochastic model predictive control |
13 |
| Sensor fault detection and isolation of an industrial gas turbine using partial adaptive KPCA |
12 |
| Regression on dynamic PLS structures for supervised learning of dynamic data |
12 |
| A review of the Expectation Maximization algorithm in data-driven process identification |
12 |
| Approaches to robust process identification: A review and tutorial of probabilistic methods |
12 |
| A deep autoencoder feature learning method for process pattern recognition |
11 |
| A novel hybrid of auto-associative kernel regression and dynamic independent component analysis for fault detection in nonlinear multimode processes |
11 |
| Adaptive virtual metrology for semiconductor chemical mechanical planarization process using GMDH-type polynomial neural networks |
11 |
| Large-scale plant-wide process modeling and hierarchical monitoring: A distributed Bayesian network approach |
11 |
| Avoiding stick slip vibrations in drilling through startup trajectory design |
11 |
| Weighted random forests for fault classification in industrial processes with hierarchical clustering model selection |
11 |
| Gaussian feature learning based on variational autoencoder for improving nonlinear process monitoring |
10 |
| An outlook on robust model predictive control algorithms: Reflections on performance and computational aspects |
10 |
| Design of sliding mode control for quadruple-tank MIMO process with time delay compensation |
9 |
| Gaussian process modelling with Gaussian mixture likelihood |
9 |
| U-model based predictive control for nonlinear processes with input delay |
9 |
| Dual robust nonlinear model predictive control: A multi-stage approach |
9 |
| Continuous control of a polymerization system with deep reinforcement learning |
8 |
| Economic nonlinear model predictive control using hybrid mechanistic data-driven models for optimal operation in real-time electricity markets: In-silico application to air separation processes |
8 |
| Scalable learning and probabilistic analytics of industrial big data based on parameter server: Framework, methods and applications |
8 |
| A feature-based soft sensor for spectroscopic data analysis |
8 |
| Comparative analysis of Granger causality and transfer entropy to present a decision flow for the application of oscillation diagnosis |
8 |
| On the application of interval PCA to process monitoring: A robust strategy for sensor FDI with new efficient control statistics |
8 |
| Interval sliding mode observer design for linear and nonlinear systems |
8 |
| Flow and pressure control of underbalanced drilling operations using NMPC |
8 |
| A geometric method for batch data visualization, process monitoring and fault detection |
8 |
| A hybrid approach for bioprocess state estimation using NIR spectroscopy and a sigma-point Kalman filter |
8 |
| Economic model predictive control of boiler-turbine system |
7 |
| Performance-based data-driven model-free adaptive sliding mode control for a class of discrete-time nonlinear processes |
7 |
| Distributed partial least squares based residual generation for statistical process monitoring |
7 |
| Incipient sensor fault diagnosis in multimode processes using conditionally independent Bayesian learning based recursive transformed component statistical analysis |
7 |
| Comprehensive process decomposition for closed-loop process monitoring with quality-relevant slow feature analysis |
7 |
| Online monitoring of performance variations and process dynamic anomalies with performance-relevant full decomposition of slow feature analysis |
7 |
| Robust bi-objective optimal control of 3-propanediol microbial batch production process |
7 |
| Reservoir characterization in under-balanced drilling using low-order lumped model |
6 |
| Industrial batch process monitoring with limited data |
6 |
| Stability analysis and design of model predictive reset control for nonlinear time-delay systems with application to a two-stage chemical reactor system |
6 |
