All Stories

  1. Adaptive hybrid modeling for chemical processes with attention mechanism
  2. Big data-driven predictive control for nonlinear systems based on kernel density estimation of data trajectories
  3. State Estimation With Model Uncertainty Using Structure Variational Bayesian and Transfer Learning
  4. Machine Learning-Based Time-Series Forecasting for Off-Gas Characterization and Decarbonization in Electric Arc Furnace Steelmaking
  5. Reinforcement learning-based autonomous control of bench-scale primary separation vessel
  6. Causal discovery in industrial systems via physics-guided variational attention and probabilistic interventions
  7. Robust soft sensing with causal and injectivity-preserving Graph Neural Network
  8. State Estimation for High-Dimensional Wastewater Treatment Plants Based on Dynamic Mode Decomposition
  9. Recursive State Estimation with Non-Negativity Constraints using Constrained Extended Kalman and Particle Filters with Truncated Distributions and Positivity-Preserving ODE Solvers
  10. Uncertainty Predictive Observer-Based Model-Free Adaptive Disturbance Rejection Control
  11. Data-Driven Closed-Loop System Fault Diagnosis Using Feedback-Invariant Dynamic Residual Analysis
  12. Robust Multimodal Sensor Fusion using Variational Autoencoder
  13. Transfer state estimator for new operation modes using variable-structure multiple models
  14. Computationally Efficient Encrypted Neuroadaptive Optimal Control for Euler–Lagrange Systems With Unknown Dynamics
  15. Reinforcement Learning-based MPC for Output Regulation of Uncertain Constrained Linear System
  16. Transfer H2 Estimation and Control of Linear Systems with Limited Data
  17. TraCPro-BDPC: Trajectory Cluster-based Probabilistic Big Data-driven Predictive Control for Nonlinear Processes
  18. Stochastic Gradient Variational Inference of Unmodeled Dynamics in State-Space With Applications
  19. A Matrix Block-Based Physics-Informed Probabilistic Quality-Relevant Monitoring Model
  20. Variational Bayesian Inference for Soft Sensor Development with Irregular Measurements
  21. Gaussian Mixture Model Aided Distribution Dissimilarity Analytics and Its Application to Robust Industrial Process Monitoring
  22. MC-RSGN: A novel soft sensor model towards high noise data in dynamic industrial polymerization processes
  23. StictionGPT: Detecting valve stiction in process control loops using large vision language model
  24. Breaking Information Granularity Heterogeneity: A Mutual Information-Inspired Causal Discovery Framework for Multi-Rate Time Series
  25. Operator-In-The-Loop Bayesian Optimization Toward Optimal Process Operation
  26. Real-time freeze point prediction using multirate measurements in the blending process
  27. A Novel Toeplitz Matrix and CNN-LSTM Based Method for Identifying Control Valve Stiction
  28. Physics-guided transfer learning for Bayesian optimization of chemical port-Hamiltonian systems
  29. M2D-VAE: Self-Supervised Probabilistic Temporal–Spatial Latent Representation Learning for Unsupervised Industrial Operational Applications Under Missing Value Interference
  30. Entropy-enhanced batch sampling and conformal learning in VGAE for physics-informed causal discovery and fault diagnosis
  31. Robust to outlier image inpainting for interface detection in primary separation vessel
  32. A Variational Bayesian Inference-Based Robust Dissimilarity Analytics Model for Industrial Fault Detection
  33. Interpretable Dynamic Modelling and Prediction of Free Acid in Zinc Leaching Process
  34. Big Data-Driven Control of Nonlinear Processes Through Dynamic Latent Variables Using an Autoencoder
  35. A Robust Probabilistic Quality-Relevant Monitoring Model With Laplace Distribution
  36. Addressing Heterogeneous Time-Frequency Causality: Source Consistency Exploring for Industrial Root Cause Alignment and Diagnosis
  37. Factor Graph Optimization for Flexibly Modeled INS/GPS Navigation in Graphical State-Space
  38. From Static and Dynamic Perspectives: A Survey on Historical Data Benchmarks of Control Performance Monitoring
  39. Causality-Informed Data-Driven Predictive Control
  40. Compensatory Data-Driven Networked Iterative Learning Control With Communication Constraints and DoS Attacks
  41. Data-Driven Iterative Learning Temperature Control for Rubber Mixing Processes
  42. EKG-AC: A New Paradigm for Process Industrial Optimization Based on Offline Reinforcement Learning With Expert Knowledge Guidance
  43. Fault-Tolerant Soft Sensor Modeling Based on a Two-Dimensional Group Distributionally Robust Optimization Framework
  44. Incremental Learning-Enabled Fault Diagnosis of Dynamic Systems: A Comprehensive Review
  45. Laplace Distribution Based Robust Identification of Errors-in-Variables Systems With Outliers
  46. Sequential Image Restoration and Segmentation for Interface Detection in Primary Separation Cells
  47. Event-Triggered Direct Data-Driven Iterative Learning Control for Multiagent Systems
  48. A Conditional Invertible Neural Network-Based Fault Detection
  49. Spatiotemporal Topology-Informed Multiagent Reinforcement Learning Framework for Structured Multiprocess Collaborative Optimization
  50. Intrinsic Causality Embedded Concurrent Quality and Process Monitoring Strategy
  51. Fast Bayesian filtering for wastewater treatment plants with inaccurate process noise statistics
  52. Bayesian-Based Causal Structure Inference With a Domain Knowledge Prior for Stable and Interpretable Soft Sensing
  53. Double-Layered Iterative Learning Control for Nonlinear Systems
  54. Data-Driven Dynamic Internal Model Control
  55. Data-Driven Finite-Iteration Learning Control
  56. Sampled-Data Model-Free Adaptive Control for Nonlinear Continuous-Time Systems
  57. Nonlinear Slow Feature Analysis for Oscillating Characteristics Under Deep Encoder-Decoder Framework
  58. Unified Unit-Wise and Plantwide Monitoring: Application in Early Detection of Gas Flare Event
  59. Detection of poor controller tuning with Gramian Angular Field (GAF) and StackAutoencoder (SAE)
  60. Digital twin and control of an industrial-scale bitumen extraction process
  61. Sparse Robust Dynamic Feature Extraction Using Bayesian Inference
  62. Bayesian Filtering for High-Dimensional State-Space Models With State Partition and Error Compensation
  63. Distributed Data-Driven Predictive Control via Dissipative Behavior Synthesis
  64. An Unsupervised Fault Detection and Diagnosis With Distribution Dissimilarity and Lasso Penalty
  65. Machine learning for industrial sensing and control: A survey and practical perspective
  66. On Approximation of System Behavior From Large Noisy Data Using Statistical Properties of Measurement Noise
  67. Robust-to-occlusion machine vision model for predicting quality variables with slow-rate measurements
  68. A Novel CVAE-Based Sequential Monte Carlo Framework for Dynamic Soft Sensor Applications
  69. Transfer Learning-Motivated Intelligent Fault Diagnosis Designs: A Survey, Insights, and Perspectives
  70. Shape-Based Pattern Recognition Approaches toward Oscillation Detection
  71. Physics‐informed sparse causal inference for source detection of plant‐wide oscillations
  72. Reinforcement Learning in Process Industries: Review and Perspective
  73. A Novel Chattering-Free Discrete Sliding Mode Controller With Disturbance Compensation for Zinc Roasting Temperature Distribution Control
  74. A Probabilistic Quality-Relevant Monitoring Method With Gaussian Mixture Model
  75. An Approach to Data-Based Linear Quadratic Optimal Control
  76. Data-Driven Internal Model Learning Control for Nonlinear Systems
  77. Data-Driven Robust Finite-Iteration Learning Control for MIMO Nonrepetitive Uncertain Systems
  78. Explainable Fault Diagnosis Using Invertible Neural Networks—Part I: A Left Manifold-Based Solution
  79. A Robust Dissimilarity Distribution Analytics With Laplace Distribution for Incipient Fault Detection
  80. Data-driven moving horizon state estimation of nonlinear processes using Koopman operator
  81. Image restoration and analysis with application to quality variable prediction in flotation process
  82. Dynamic Linearization and Extended State Observer-Based Data-Driven Adaptive Control
  83. Fault-Tolerant Soft Sensors for Dynamic Systems
  84. Hammerstein–Wiener Model Identification for Oil-in-Water Separation Dynamics in a De-Oiling Hydrocyclone System
  85. Fault Detection for Nonlinear Dynamic Systems With Consideration of Modeling Errors: A Data-Driven Approach
  86. Data-Driven Virtual Reference Set-Point Learning of PD Control and Applications to Permanent Magnet Linear Motors
  87. Double Dynamic Linearization-Based Higher Order Indirect Adaptive Iterative Learning Control
  88. Generalized Robust MPC with zone-tracking
  89. Variational Bayesian Inference for Robust Identification of PWARX Systems With Time-Varying Time-Delays
  90. Reinforcement learning for soft sensor design through autonomous cross-domain data selection
  91. Statistical Test-Based Practical Methods for Detection and Quantification of Stiction in Control Valves
  92. Enhanced P-Type Control: Indirect Adaptive Learning From Set-Point Updates
  93. A Transferable Multistage Model With Cycling Discrepancy Learning for Lithium-Ion Battery State of Health Estimation
  94. Process Monitoring Using Domain-Adversarial Probabilistic Principal Component Analysis: A Transfer Learning Framework
  95. Deep Bayesian Slow Feature Extraction With Application to Industrial Inferential Modeling
  96. No-Delay Multimodal Process Monitoring Using Kullback-Leibler Divergence-Based Statistics in Probabilistic Mixture Models
  97. Tuning-Free Bayesian Estimation Algorithms for Faulty Sensor Signals in State-Space
  98. ConvLSTM and Self-Attention Aided Canonical Correlation Analysis for Multioutput Soft Sensor Modeling
  99. Data-Driven Indirect Iterative Learning Control
  100. Explicit Representation and Customized Fault Isolation Framework for Learning Temporal and Spatial Dependencies in Industrial Processes
  101. Identification of Errors-in-Variable System With Heteroscedastic Noise and Partially Known Input Using Variational Bayesian
  102. Skew Filtering for Online State Estimation and Control
  103. Variational Bayesian Approach to Nonstationary and Oscillatory Slow Feature Analysis With Applications in Soft Sensing and Process Monitoring
  104. Smart Optimization with Ppcr Modeling in the Presence of Missing Data, Time Delay and Model-Plant Mismatch
  105. A Deep Probabilistic Transfer Learning Framework for Soft Sensor Modeling With Missing Data
  106. Variational Progressive-Transfer Network for Soft Sensing of Multirate Industrial Processes
  107. Transfer Learning for Dynamic Feature Extraction Using Variational Bayesian Inference
  108. Data-Driven Designs of Fault Detection Systems via Neural Network-Aided Learning
  109. Event-Triggered Distributed Moving Horizon State Estimation of Linear Systems
  110. A Single-Side Neural Network-Aided Canonical Correlation Analysis With Applications to Fault Diagnosis
  111. Event-Triggered ILC for Optimal Consensus at Specified Data Points of Heterogeneous Networked Agents With Switching Topologies
  112. Multisource-Refined Transfer Network for Industrial Fault Diagnosis Under Domain and Category Inconsistencies
  113. Data-Driven Adaptive Consensus Learning From Network Topologies
  114. Discrete-Time-Distributed Adaptive ILC With Nonrepetitive Uncertainties and Applications to Building HVAC Systems
  115. MoniNet With Concurrent Analytics of Temporal and Spatial Information for Fault Detection in Industrial Processes
  116. Overexpression of heat shock protein 70 induces apoptosis of intestinal epithelial cells in heat-stressed pigs: A proteomics approach
  117. Parallel Interaction Spatiotemporal Constrained Variational Autoencoder for Soft Sensor Modeling
  118. Community detection based process decomposition and distributed monitoring for large‐scale processes
  119. Data-Driven Communication Efficient Distributed Monitoring for Multiunit Industrial Plant-Wide Processes
  120. Offline and Online Parameter Learning for Switching Multirate Processes With Varying Delays and Integrated Measurements
  121. Reinforcement Learning With Constrained Uncertain Reward Function Through Particle Filtering
  122. Quantitative Data-Driven Adaptive Iterative Learning Control: From Trajectory Tracking to Point-to-Point Tracking
  123. Reinforcement learning approach to autonomous PID tuning
  124. Sparse Inverse Covariance Estimation for Causal Inference in Process Data Analytics
  125. Robust probabilistic principal component regression with switching mixture Gaussian noise for soft sensing
  126. Sensor Fault Estimation in a Probabilistic Framework for Industrial Processes and its Applications
  127. Spatial Linear Dynamic Relationship of Strongly Connected Multiagent Systems and Adaptive Learning Control for Different Formations
  128. Data-Driven Adaptive Iterative Learning Bipartite Consensus for Heterogeneous Nonlinear Cooperation-Antagonism Networks
  129. Distributed Process Monitoring for Multi-Agent Systems Through Cognitive Learning
  130. Explainable Intelligent Fault Diagnosis for Nonlinear Dynamic Systems: From Unsupervised to Supervised Learning
  131. Incremental Variational Bayesian Gaussian Mixture Model With Decremental Optimization for Distribution Accommodation and Fine-Scale Adaptive Process Monitoring
  132. Multirate Sensor Fusion in the Presence of Irregular Measurements and Time-Varying Time Delays Using Synchronized, Neural, Extended Kalman Filters
  133. Robust Variational Bayesian-Based Soft Sensor Model for LPV Processes With Delayed and Integrated Output Measurements
  134. Sparse and Time-Varying Predictive Relation Extraction for Root Cause Quantification of Nonstationary Process Faults
  135. Practical Linear Regression-Based Method for Detection and Quantification of Stiction in Control Valves
  136. A Gaussian mixture model based virtual sample generation approach for small datasets in industrial processes
  137. Active Disturbance Rejection Control for Nonaffined Globally Lipschitz Nonlinear Discrete-Time Systems
  138. Adversarial smoothing tri-regression for robust semi-supervised industrial soft sensor
  139. Latent variable modeling and state estimation of non-stationary processes driven by monotonic trends
  140. Observer-Based Sampled-Data Model-Free Adaptive Control for Continuous-Time Nonlinear Nonaffine Systems With Input Rate Constraints
  141. Event-Triggered Nonlinear Iterative Learning Control
  142. State Estimation for Multirate Measurements in the Presence of Integral Term and Variable Delay
  143. A Holistic Probabilistic Framework for Monitoring Nonstationary Dynamic Industrial Processes
  144. Online Probabilistic Estimation of Sensor Faulty Signal in Industrial Processes and Its Applications
  145. Siamese Neural Network-Based Supervised Slow Feature Extraction for Soft Sensor Application
  146. Data-driven multi-model minimum variance controller design based on support vectors
  147. Identification of Two-Dimensional Causal Systems With Missing Output Data via Expectation–Maximization Algorithm
  148. Online reinforcement learning for a continuous space system with experimental validation
  149. Auxiliary Predictive Compensation-Based ILC for Variable Pass Lengths
  150. Convergence Analysis of Sampled-Data ILC for Locally Lipschitz Continuous Nonlinear Nonaffine Systems With Nonrepetitive Uncertainties
  151. Mixture robust semi-supervised probabilistic principal component regression with missing input data
  152. Two-stage time-varying hidden conditional random fields with variable selection for process operating mode diagnosis
  153. Event-Triggered Model-Free Adaptive Control
  154. Parameter estimation for nonlinear systems with multirate measurements and random delays
  155. A Variational Bayesian Causal Analysis Approach for Time-Varying Systems
  156. Soft sensor based on eXtreme gradient boosting and bidirectional converted gates long short-term memory self-attention network
  157. Extended State Observer-Based Data-Driven Iterative Learning Control for Permanent Magnet Linear Motor With Initial Shifts and Disturbances
  158. Multimodal process monitoring based on variational Bayesian PCA and Kullback-Leibler divergence between mixture models
  159. Valve Stiction Detection and Quantification Using a K-Means Clustering Based Moving Window Approach
  160. Forward–Backward Smoothers With Finite Impulse Response Structure
  161. Hidden Markov Model-Based Attack Detection for Networked Control Systems Subject to Random Packet Dropouts
  162. Stationary Subspace Analysis-Based Hierarchical Model for Batch Processes Monitoring
  163. Data-Driven Fault Detection for Dynamic Systems With Performance Degradation: A Unified Transfer Learning Framework
  164. Dual Neural Extended Kalman Filtering Approach for Multirate Sensor Data Fusion
  165. Kalman Filter-Based Convolutional Neural Network for Robust Tracking of Froth-Middling Interface in a Primary Separation Vessel in Presence of Occlusions
  166. Consensus‐based approach for parameter and state estimation of agro‐hydrological systems
  167. Adjacent-Agent Dynamic Linearization-Based Iterative Learning Formation Control
  168. Discrete-Time Extended State Observer-Based Model-Free Adaptive Control Via Local Dynamic Linearization
  169. Data-Driven Modeling Based on Two-Stream ${\rm{\lambda }}$ Gated Recurrent Unit Network With Soft Sensor Application
  170. Hierarchical Quality-Relevant Feature Representation for Soft Sensor Modeling: A Novel Deep Learning Strategy
  171. Real-Time Mode Diagnosis for Processes With Multiple Operating Conditions Using Switching Conditional Random Fields
  172. Gaussian process regression with heteroscedastic noises — A machine-learning predictive variance approach
  173. Distributed data‐driven observer for linear time invariant systems
  174. Supervised Variational Autoencoders for Soft Sensor Modeling With Missing Data
  175. Detecting the Direction of Information Flow in Instantaneous Relations Between Variables
  176. Iterative Identification of Hammerstein Parameter Varying Systems With Parameter Uncertainties Based on the Variational Bayesian Approach
  177. 3-D Learning-Enhanced Adaptive ILC for Iteration-Varying Formation Tasks
  178. Probabilistic just-in-time approach for nonlinear modeling with Bayesian nonlinear feature extraction
  179. Distributed control performance assessment and corresponding optimal controller design considering communication delays
  180. Neighborhood Variational Bayesian Multivariate Analysis for Distributed Process Monitoring With Missing Data
  181. Feature Extraction of Constrained Dynamic Latent Variables
  182. Simultaneous Static and Dynamic Analysis for Fine-Scale Identification of Process Operation Statuses
  183. Review and Perspectives of Data-Driven Distributed Monitoring for Industrial Plant-Wide Processes
  184. Variational Bayesian Approach for Causality and Contemporaneous Correlation Features Inference in Industrial Process Data
  185. A new soft-sensor algorithm with concurrent consideration of slowness and quality interpretation for dynamic chemical process
  186. Robust filter design for asymmetric measurement noise using variational Bayesian inference
  187. Parameter estimation of Markov-switching Hammerstein systems using variational Bayesian approach
  188. An Improved Data-Driven Point-to-Point ILC Using Additional On-Line Control Inputs With Experimental Verification
  189. Data rectification for multiple operating modes: A MAP framework
  190. Multiple-Model State Estimation Based on Variational Bayesian Inference
  191. Mixtures of Probabilistic PCA With Common Structure Latent Bases for Process Monitoring
  192. Probabilistic Monitoring of Sensors in State-Space With Variational Bayesian Inference
  193. Hierarchically Distributed Monitoring for the Early Prediction of Gas Flare Events
  194. Distributed multiple step ahead prediction considering communication delays
  195. Robust FIR State Estimation of Dynamic Processes Corrupted by Outliers
  196. Deep Discriminative Representation Learning for Nonlinear Process Fault Detection
  197. Semi‐supervised dynamic latent variable modeling: I/O probabilistic slow feature analysis approach
  198. Computationally Efficient Data-Driven Higher Order Optimal Iterative Learning Control
  199. Multivariate Gaussian process regression for nonlinear modelling with colored noise
  200. Chance-Constrained Model Predictive Control for SAGD Process Using Robust Optimization Approximation
  201. An Augmented Model Approach for Identification of Nonlinear Errors-in-Variables Systems Using the EM Algorithm
  202. Recursive Slow Feature Analysis for Adaptive Monitoring of Industrial Processes
  203. Distributed Dynamic Modeling and Monitoring for Large-Scale Industrial Processes under Closed-Loop Control
  204. Control Performance Assessment for ILC-Controlled Batch Processes in a 2-D System Framework
  205. Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE
  206. Approaches to robust process identification: A review and tutorial of probabilistic methods
  207. Localization of Indoor Mobile Robot Using Minimum Variance Unbiased FIR Filter
  208. Distributed Student's t filtering algorithm for heavy-tailed noises
  209. Incipient Fault Detection for Complex Industrial Processes with Stationary and Nonstationary Hybrid Characteristics
  210. A novel approach to process operating mode diagnosis using conditional random fields in the presence of missing data
  211. Robust Estimation of ARX Models With Time Varying Time Delays Using Variational Bayesian Approach
  212. Minimum Variance Bound and Minimum Variance Controller for Convex Nonlinear Systems with Input Constraints
  213. Extracting dynamic features with switching models for process data analytics and application in soft sensing
  214. Triggered Communication in Distributed Adaptive High-Gain EKF
  215. A full-condition monitoring method for nonstationary dynamic chemical processes with cointegration and slow feature analysis
  216. Molecular-Based Bayesian Regression Model of Petroleum Fractions
  217. Expectation Maximization Approach for Simultaneous Gross Error Detection and Data Reconciliation Using Gaussian Mixture Distribution
  218. Robust Identification of Nonlinear Errors-in-Variables Systems With Parameter Uncertainties Using Variational Bayesian Approach
  219. Iteration Tuning of Disturbance Observer-Based Control System Satisfying Robustness Index for FOPTD Processes
  220. A Data-Based Augmented Model Identification Method for Linear Errors-in-Variables Systems Based on EM Algorithm
  221. Iterative Residual Generator for Fault Detection With Linear Time-Invariant State–Space Models
  222. Nonlinear robust optimization for process design
  223. Detection and Diagnosis of Multiple Faults With Uncertain Modeling Parameters
  224. Interaction Analysis of Multivariate Control Systems Under Bayesian Framework
  225. Bayesian Learning for Dynamic Feature Extraction With Application in Soft Sensing
  226. An E-HOIM Based Data-Driven Adaptive TILC of Nonlinear Discrete-Time Systems for Non-Repetitive Terminal Point Tracking
  227. Mixture semisupervised probabilistic principal component regression model with missing inputs
  228. Computationally-Light Non-Lifted Data-Driven Norm-Optimal Iterative Learning Control
  229. Data-driven high-order terminal iterative learning control with a faster convergence speed
  230. Distributed adaptive high-gain extended Kalman filtering for nonlinear systems
  231. A Probabilistic Just-in-Time Learning Framework for Soft Sensor Development With Missing Data
  232. A Data-Driven Hybrid ARX and Markov Chain Modeling Approach to Process Identification With Time-Varying Time Delays
  233. Semisupervised JITL Framework for Nonlinear Industrial Soft Sensing Based on Locally Semisupervised Weighted PCR
  234. Wavelet Transform Based Methodology for Detection and Characterization of Multiple Oscillations in Nonstationary Variables
  235. Adaptive soft sensor based on time difference Gaussian process regression with local time-delay reconstruction
  236. Distributed monitoring for large-scale processes based on multivariate statistical analysis and Bayesian method
  237. JITL based MWGPR soft sensor for multi-mode process with dual-updating strategy
  238. Robust probabilistic principal component analysis for process modeling subject to scaled mixture Gaussian noise
  239. Robust Gaussian process modeling using EM algorithm
  240. Double locally weighted principal component regression for soft sensor with sample selection under supervised latent structure
  241. New results on the robust stability of PID controllers with gain and phase margins for UFOPTD processes
  242. Slow feature analysis for monitoring and diagnosis of control performance
  243. Dynamic higher-order cumulants analysis for state monitoring based on a novel lag selection
  244. Monitoring of operating point and process dynamics via probabilistic slow feature analysis
  245. Predicting GHS toxicity using RTCA and discrete-time Fourier transform
  246. Robust Diagnosis of Operating Mode Based on Time-Varying Hidden Markov Models
  247. Robust optimization under correlated uncertainty: Formulations and computational study
  248. GMM and optimal principal components-based Bayesian method for multimode fault diagnosis
  249. Performance-Driven Distributed PCA Process Monitoring Based on Fault-Relevant Variable Selection and Bayesian Inference
  250. Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems
  251. Predicting wellbore dynamics in a steam-assisted gravity drainage system: Numeric and semi-analytic model, and validation
  252. Generalized expectation–maximization approach to LPV process identification with randomly missing output data
  253. Optimal continuous-time state estimation for linear finite and infinite-dimensional chemical process systems with state constraints
  254. Process monitoring using kernel density estimation and Bayesian networking with an industrial case study
  255. Fault Detection and Diagnosis of Multiple-Model Systems With Mismodeled Transition Probabilities
  256. State estimation incorporating infrequent, delayed and integral measurements
  257. Probabilistic slow feature analysis-based representation learning from massive process data for soft sensor modeling
  258. Diagnosis of Oscillations Between Controller Tuning and Harmonic External Disturbances
  259. A unified data-driven design framework of optimality-based generalized iterative learning control
  260. Nonlinear process identification in the presence of multiple correlated hidden scheduling variables with missing data
  261. Bayesian method for simultaneous gross error detection and data reconciliation
  262. Analysis of inter-/intra-E-plate repeatability in the real-time cell analyzer
  263. High-throughput screening assay for the environmental water samples using cellular response profiles
  264. A Bayesian sparse reconstruction method for fault detection and isolation
  265. Minimum variance unbiased FIR filter for discrete time-variant systems
  266. Minimal required excitation for closed-loop identification: Some implications for data-driven, system identification
  267. Process monitoring based on factor analysis: Probabilistic analysis of monitoring statistics in presence of both complete and incomplete measurements
  268. Expectation–Maximization Approach to Fault Diagnosis With Missing Data
  269. Detecting and isolating abrupt changes in linear switching systems
  270. Bias-eliminated subspace model identification under time-varying deterministic type load disturbance
  271. State Estimation in Batch Process Based on Two-Dimensional State-Space Model
  272. Adaptive monitoring of the process operation based on symbolic episode representation and hidden Markov models with application toward an oil sand primary separation
  273. Multi-input–Multi-output (MIMO) Control System Performance Monitoring Based on Dissimilarity Analysis
  274. A Bayesian framework for real-time identification of locally weighted partial least squares
  275. Operating condition diagnosis based on HMM with adaptive transition probabilities in presence of missing observations
  276. Development of soft sensor by incorporating the delayed infrequent and irregular measurements
  277. Frequency analysis and compensation of valve stiction in cascade control loops
  278. Model predictive control of axial dispersion chemical reactor
  279. Expectation Maximization method for multivariate change point detection in presence of unknown and changing covariance
  280. Parameter estimation for a dual-rate system with time delay
  281. Robust multiple-model LPV approach to nonlinear process identification using mixture t distributions
  282. A unified recursive just-in-time approach with industrial near infrared spectroscopy application
  283. Multiple-Model Based Linear Parameter Varying Time-Delay System Identification with Missing Output Data Using an Expectation-Maximization Algorithm
  284. Performance Assessment of Industrial Linear Controllers in Univariate Control Loops for Both Set Point Tracking and Load Disturbance Rejection
  285. Nonlinear semisupervised principal component regression for soft sensor modeling and its mixture form
  286. Recursive constrained state estimation using modified extended Kalman filter
  287. Automatic Detection and Frequency Estimation of Oscillatory Variables in the Presence of Multiple Oscillations
  288. A probabilistic framework for real-time performance assessment of inferential sensors
  289. Control-loop diagnosis using continuous evidence through kernel density estimation
  290. Mode of action classification of chemicals using multi-concentration time-dependent cellular response profiles
  291. Inequality constrained parameter estimation using filtering approaches
  292. Constrained particle filtering methods for state estimation of nonlinear process
  293. Performance assessment, diagnosis, and optimal selection of non-linear state filters
  294. Bayesian Control Loop Diagnosis by Combining Historical Data and Process Knowledge of Fault Signatures
  295. Bayesian and Expectation Maximization methods for multivariate change point detection
  296. In vitro cytotoxicity assessment based on KC50 with real-time cell analyzer (RTCA) assay
  297. Mixture semisupervised principal component regression model and soft sensor application
  298. Control loop diagnosis with ambiguous historical operating modes: Part 2, information synthesis based on proportional parametrization
  299. Design of inferential sensors in the process industry: A review of Bayesian methods
  300. Moving horizon estimation for switching nonlinear systems
  301. Information transfer methods in causality analysis of process variables with an industrial application
  302. Parameter estimation in batch process using EM algorithm with particle filter
  303. Statistical properties of signal entropy for use in detecting changes in time series data
  304. Data quality assessment of routine operating data for process identification
  305. Model Predictive Control: Algorithmic Development and Applications
  306. Soft sensors for online steam quality measurements of OTSGs
  307. FIR model identification of multirate processes with random delays using EM algorithm
  308. A moving horizon approach to a noncontinuum state estimation
  309. Bayesian method for state estimation of batch process with missing data
  310. Recursive Wavelength-Selection Strategy to Update Near-Infrared Spectroscopy Model with an Industrial Application
  311. Improved DCT-based method for online detection of oscillations in univariate time series
  312. Soft sensor solutions for control of oil sands processes
  313. Control loop diagnosis with ambiguous historical operating modes: Part 1. A proportional parametrization approach
  314. On simultaneous on-line state and parameter estimation in non-linear state-space models
  315. Development and industrial application of soft sensors with on-line Bayesian model updating strategy
  316. Cytotoxicity assessment based on the AUC50 using multi-concentration time-dependent cellular response curves
  317. A Bayesian approach to design of adaptive multi-model inferential sensors with application in oil sand industry
  318. 4th Symposium on Advanced Control of Industrial Processes (ADCONIP)
  319. Compensation of control valve stiction through controller tuning
  320. 4th Symposium on advanced control of industrial processes (Adconip)
  321. High-throughput quantitative analysis with cell growth kinetic curves for low copy number mutant cells
  322. A Bayesian approach to robust process identification with ARX models
  323. Guest Editorial: 4TH symposium on advanced control of industrial processes (ADCONIP)
  324. Deterministic vs. stochastic performance assessment of iterative learning control for batch processes
  325. Microelectronic-sensing assay to detect presence of Verotoxins in human faecal samples
  326. Dual particle filters for state and parameter estimation with application to a run-of-mine ore mill
  327. Recognition of chemical compounds in contaminated water using time-dependent multiple dose cellular responses
  328. Tuning a Soft Sensor’s Bias Update Term. 1. The Open-Loop Case
  329. Tuning a Soft Sensor’s Bias Update Term. 2. The Closed-Loop Case
  330. Estimation of bitumen froth quality using Bayesian information synthesis: An application to froth transportation process
  331. Identification of nonlinear parameter varying systems with missing output data
  332. Model analysis and performance analysis of two industrial MPCs
  333. On-line estimation of glucose and biomass concentration in batch fermentation process using particle filter with constraint
  334. Designing priors for robust Bayesian optimal experimental design
  335. Identification of switched Markov autoregressive eXogenous systems with hidden switching state
  336. Multiple model based LPV soft sensor development with irregular/missing process output measurement
  337. Dynamic bayesian approach to gross error detection and compensation with application toward an oil sands process
  338. Prediction error method for identification of LPV models
  339. Solid oxide fuel cell: Perspective of dynamic modeling and control
  340. Determining the state of a process control system: Current trends and future challenges
  341. Dynamic output feedback robust model predictive control
  342. Estimation of distribution function for control valve stiction estimation
  343. Performance assessment of PID control loops subject to setpoint changes
  344. Closed-loop identification with routine operating data: Effect of time delay and sampling time
  345. Bayesian methods for control loop diagnosis in the presence of temporal dependent evidences
  346. Closed-loop identification condition for ARMAX models using routine operating data
  347. Control Performance Assessment Subject to Multi-Objective User-Specified Performance Characteristics
  348. Development of a simultaneous continuum and noncontinuum state estimator with application on a distillation process
  349. Estimation of Instrument Variance and Bias Using Bayesian Methods
  350. Real-time cell-impedance sensing assay as an alternative to clonogenic assay in evaluating cancer radiotherapy
  351. Data-based modeling and prediction of cytotoxicity induced by contaminants in water resources
  352. Determining the Harmonic Impacts of Multiple Harmonic-Producing Loads
  353. Reconciling continuum and non-continuum data with industrial application
  354. Monitoring of solid oxide fuel cell systems
  355. A decoupled multiple model approach for soft sensors design
  356. Multiple model LPV approach to nonlinear process identification with EM algorithm
  357. Constrained receding-horizon experiment design and parameter estimation in the presence of poor initial conditions
  358. Subspace Approach to Identification of Step-Response Model from Closed-Loop Data
  359. Performance assessment of advanced supervisory–regulatory control systems with subspace LQG benchmark
  360. Dynamic Bayesian Approach for Control Loop Diagnosis with Underlying Mode Dependency
  361. Bayesian method for multirate data synthesis and model calibration
  362. The DCT-based oscillation detection method for a single time series
  363. Early determination of toxicant concentration in water supply using MHE
  364. Online composition estimation and experiment validation of distillation processes with switching dynamics
  365. Constrained Bayesian state estimation – A comparative study and a new particle filter based approach
  366. Industrial implementation of controller performance analysis technology
  367. Estimation and control of solid oxide fuel cell system
  368. Multi-step prediction error approach for controller performance monitoring
  369. Stiction Estimation Using Constrained Optimisation and Contour Map
  370. Consistency of noise covariance estimation in joint input–output closed-loop subspace identification with application in LQG benchmarking
  371. Robust identification of switched regression models
  372. Robust identification of piecewise/switching autoregressive exogenous process
  373. Implementation of FIR control for H ∞ output feedback stabilisation of linear systems
  374. Subspace method aided data-driven design of fault detection and isolation systems
  375. H∞structured model reduction algorithms for linear discrete systems via LMI-based optimisation
  376. Identification of Hammerstein systems without explicit parameterisation of non-linearity
  377. Closed-loop model validation based on the two-model divergence method
  378. Economic performance assessment of advanced process control with LQG benchmarking
  379. MPC Constraint Analysis—Bayesian Approach via a Continuous-Valued Profit Function
  380. Identifiability and estimability study for a dynamic solid oxide fuel cell model
  381. Preferential crystallization: Multi-objective optimization framework
  382. Validation of continuous-time models with delay
  383. A Bayesian approach for control loop diagnosis with missing data
  384. Dealing with Irregular Data in Soft Sensors: Bayesian Method and Comparative Study
  385. Bayesian methods for control loop monitoring and diagnosis
  386. Robust H2 optimal filtering for con...
  387. Sensitivity analysis for selective constraint and variability tuning in performance assessment of industrial MPC
  388. Control relevant on-line model validation criterion based on robust stability conditions
  389. Performance assessment of MIMO control systems with time-variant disturbance dynamics
  390. Reformulation of LMI-based stabilisation conditions for non-linear systems in Takagi–Sugeno's form
  391. Identification from step responses with transient initial conditions
  392. 1-D dynamic modeling of SOFC with analytical solution for reacting gas-flow problem
  393. Dynamics and variance control of hot mill loopers
  394. Assessing Model Prediction Control (MPC) Performance. 1. Probabilistic Approach for Constraint Analysis
  395. Assessing Model Prediction Control (MPC) Performance. 2. Bayesian Approach for Constraint Tuning
  396. Output feedback model predictive control for nonlinear systems represented by Hammerstein–Wiener model
  397. New formulation of robust MPC by incorporating off-line approach with on-line optimization
  398. Comments on "A Feedback Min-Max MPC Algorithm for LPV Systems Subject to Bounded Rates of Change of Parameters
  399. Novel identification method from step response
  400. Constrained approximation of multiple input–output delay systems using genetic algorithm
  401. Constrained robust model predictive control for time-delay systems with polytopic description
  402. A blind approach to closed-loop identification of Hammerstein systems
  403. Data-driven predictive control for solid oxide fuel cells
  404. Performance Assessment of Model Pedictive Control for Variability and Constraint Tuning
  405. Control relevant modeling of planer solid oxide fuel cell system
  406. FIR modelling for errors-in-variables/closed-loop systems by exploiting cyclo-stationarity
  407. Improved identification of continuous-time delay processes from piecewise step tests
  408. Multirate Minimum Variance Control Design and Control Performance Assessment: A Data-Driven Subspace Approach
  409. Monitoring control performance via structured closed-loop response subject to output variance/covariance upper bound
  410. Dynamic modeling of a finite volume of solid oxide fuel cell: The effect of transport dynamics
  411. Performance monitoring of SISO control loops subject to LTV disturbance dynamics: An improved LTI benchmark
  412. Alternative solutions to multi-variate control performance assessment problems
  413. Parameter and delay estimation of continuous-time models using a linear filter
  414. Cyclo-period estimation for discrete-time cyclo-stationary signals
  415. Model Reduction of Uncertain Systems with Multiplicative Noise Based on Balancing
  416. Stochastic stability and robust control for sampled-data systems with Markovian jump parameters
  417. Dynamic modeling of solid oxide fuel cell: The effect of diffusion and inherent impedance
  418. Closed-loop identification with a quantizer
  419. A new method for stabilization of networked control systems with random delays
  420. Multirate robust digital control for fuzzy systems with periodic Lyapunov function
  421. Practical solutions to multivariate feedback control performance assessment problem: reduced a priori knowledge of interactor matrices
  422. On spectral theory of cyclostationary signals in multirate systems
  423. Closed-loop subspace identification: an orthogonal projection approach
  424. Fixed-order controller design for linear time-invariant descriptor systems: A BMI approach
  425. Minimum variance in fast, slow and dual-rate control loops
  426. Performance assessment and robustness analysis using an ARMarkov approach
  427. H2 approximation of multiple input/output delay systems
  428. Closed-loop identification via output fast sampling
  429. Robust Model Predictive Control of Singular Systems
  430. Robust Digital Model Predictive Control for Linear Uncertain Systems With Saturations
  431. Multirate sampled-data systems: computing fast-rate models
  432. Feedforward and Feedback Controller Performance Assessment of Linear Time-Variant Processes
  433. Industrial Applications of a Feedback Controller Performance Assessment of Time-Variant Processes
  434. Performance evaluation of two industrial MPC controllers
  435. H∞ model reduction of Markovian jump linear systems
  436. LMI synthesis of H/sup 2/ and mixed H/sub 2//H/sub ∞/ controllers for singular systems
  437. Model predictive control relevant identification and validation
  438. Improved Threshold for the Local Approach in Detecting Faults
  439. A pragmatic approach towards assessment of control loop performance
  440. Controller performance assessment in set point tracking and regulatory control
  441. On gramians and balanced truncation of discrete-time bilinear systems
  442. Estimation of the Dynamic Matrix and Noise Model for Model Predictive Control Using Closed-Loop Data