All Stories

  1. A Robust Dissimilarity Distribution Analytics With Laplace Distribution for Incipient Fault Detection
  2. Fault Detection for Nonlinear Dynamic Systems With Consideration of Modeling Errors: A Data-Driven Approach
  3. Data-Driven Virtual Reference Set-Point Learning of PD Control and Applications to Permanent Magnet Linear Motors
  4. Double Dynamic Linearization-Based Higher Order Indirect Adaptive Iterative Learning Control
  5. Generalized Robust MPC with zone-tracking
  6. Variational Bayesian Inference for Robust Identification of PWARX Systems With Time-Varying Time-Delays
  7. Reinforcement learning for soft sensor design through autonomous cross-domain data selection
  8. Statistical Test-Based Practical Methods for Detection and Quantification of Stiction in Control Valves
  9. Enhanced P-Type Control: Indirect Adaptive Learning From Set-Point Updates
  10. A Transferable Multistage Model With Cycling Discrepancy Learning for Lithium-Ion Battery State of Health Estimation
  11. Process Monitoring Using Domain-Adversarial Probabilistic Principal Component Analysis: A Transfer Learning Framework
  12. Deep Bayesian Slow Feature Extraction With Application to Industrial Inferential Modeling
  13. No-Delay Multimodal Process Monitoring Using Kullback-Leibler Divergence-Based Statistics in Probabilistic Mixture Models
  14. Tuning-Free Bayesian Estimation Algorithms for Faulty Sensor Signals in State-Space
  15. ConvLSTM and Self-Attention Aided Canonical Correlation Analysis for Multioutput Soft Sensor Modeling
  16. Data-Driven Indirect Iterative Learning Control
  17. Explicit Representation and Customized Fault Isolation Framework for Learning Temporal and Spatial Dependencies in Industrial Processes
  18. Identification of Errors-in-Variable System With Heteroscedastic Noise and Partially Known Input Using Variational Bayesian
  19. Skew Filtering for Online State Estimation and Control
  20. Variational Bayesian Approach to Nonstationary and Oscillatory Slow Feature Analysis With Applications in Soft Sensing and Process Monitoring
  21. A Deep Probabilistic Transfer Learning Framework for Soft Sensor Modeling With Missing Data
  22. Variational Progressive-Transfer Network for Soft Sensing of Multirate Industrial Processes
  23. Transfer Learning for Dynamic Feature Extraction Using Variational Bayesian Inference
  24. Data-Driven Designs of Fault Detection Systems via Neural Network-Aided Learning
  25. Event-Triggered Distributed Moving Horizon State Estimation of Linear Systems
  26. A Single-Side Neural Network-Aided Canonical Correlation Analysis With Applications to Fault Diagnosis
  27. Event-Triggered ILC for Optimal Consensus at Specified Data Points of Heterogeneous Networked Agents With Switching Topologies
  28. Multisource-Refined Transfer Network for Industrial Fault Diagnosis Under Domain and Category Inconsistencies
  29. Data-Driven Adaptive Consensus Learning From Network Topologies
  30. Discrete-Time-Distributed Adaptive ILC With Nonrepetitive Uncertainties and Applications to Building HVAC Systems
  31. MoniNet With Concurrent Analytics of Temporal and Spatial Information for Fault Detection in Industrial Processes
  32. Overexpression of heat shock protein 70 induces apoptosis of intestinal epithelial cells in heat-stressed pigs: A proteomics approach
  33. Parallel Interaction Spatiotemporal Constrained Variational Autoencoder for Soft Sensor Modeling
  34. Community detection based process decomposition and distributed monitoring for large‐scale processes
  35. Data-Driven Communication Efficient Distributed Monitoring for Multiunit Industrial Plant-Wide Processes
  36. Offline and Online Parameter Learning for Switching Multirate Processes With Varying Delays and Integrated Measurements
  37. Reinforcement Learning With Constrained Uncertain Reward Function Through Particle Filtering
  38. Quantitative Data-Driven Adaptive Iterative Learning Control: From Trajectory Tracking to Point-to-Point Tracking
  39. Reinforcement learning approach to autonomous PID tuning
  40. Sparse Inverse Covariance Estimation for Causal Inference in Process Data Analytics
  41. Robust probabilistic principal component regression with switching mixture Gaussian noise for soft sensing
  42. Sensor Fault Estimation in a Probabilistic Framework for Industrial Processes and its Applications
  43. Spatial Linear Dynamic Relationship of Strongly Connected Multiagent Systems and Adaptive Learning Control for Different Formations
  44. Data-Driven Adaptive Iterative Learning Bipartite Consensus for Heterogeneous Nonlinear Cooperation-Antagonism Networks
  45. Distributed Process Monitoring for Multi-Agent Systems Through Cognitive Learning
  46. Explainable Intelligent Fault Diagnosis for Nonlinear Dynamic Systems: From Unsupervised to Supervised Learning
  47. Incremental Variational Bayesian Gaussian Mixture Model With Decremental Optimization for Distribution Accommodation and Fine-Scale Adaptive Process Monitoring
  48. Multirate Sensor Fusion in the Presence of Irregular Measurements and Time-Varying Time Delays Using Synchronized, Neural, Extended Kalman Filters
  49. Robust Variational Bayesian-Based Soft Sensor Model for LPV Processes With Delayed and Integrated Output Measurements
  50. Sparse and Time-Varying Predictive Relation Extraction for Root Cause Quantification of Nonstationary Process Faults
  51. Practical Linear Regression-Based Method for Detection and Quantification of Stiction in Control Valves
  52. A Gaussian mixture model based virtual sample generation approach for small datasets in industrial processes
  53. Active Disturbance Rejection Control for Nonaffined Globally Lipschitz Nonlinear Discrete-Time Systems
  54. Adversarial smoothing tri-regression for robust semi-supervised industrial soft sensor
  55. Latent variable modeling and state estimation of non-stationary processes driven by monotonic trends
  56. Observer-Based Sampled-Data Model-Free Adaptive Control for Continuous-Time Nonlinear Nonaffine Systems With Input Rate Constraints
  57. Event-Triggered Nonlinear Iterative Learning Control
  58. State Estimation for Multirate Measurements in the Presence of Integral Term and Variable Delay
  59. A Holistic Probabilistic Framework for Monitoring Nonstationary Dynamic Industrial Processes
  60. Online Probabilistic Estimation of Sensor Faulty Signal in Industrial Processes and Its Applications
  61. Siamese Neural Network-Based Supervised Slow Feature Extraction for Soft Sensor Application
  62. Data-driven multi-model minimum variance controller design based on support vectors
  63. Identification of Two-Dimensional Causal Systems With Missing Output Data via Expectation–Maximization Algorithm
  64. Online reinforcement learning for a continuous space system with experimental validation
  65. Auxiliary Predictive Compensation-Based ILC for Variable Pass Lengths
  66. Convergence Analysis of Sampled-Data ILC for Locally Lipschitz Continuous Nonlinear Nonaffine Systems With Nonrepetitive Uncertainties
  67. Mixture robust semi-supervised probabilistic principal component regression with missing input data
  68. Two-stage time-varying hidden conditional random fields with variable selection for process operating mode diagnosis
  69. Event-Triggered Model-Free Adaptive Control
  70. Parameter estimation for nonlinear systems with multirate measurements and random delays
  71. A Variational Bayesian Causal Analysis Approach for Time-Varying Systems
  72. Soft sensor based on eXtreme gradient boosting and bidirectional converted gates long short-term memory self-attention network
  73. Extended State Observer-Based Data-Driven Iterative Learning Control for Permanent Magnet Linear Motor With Initial Shifts and Disturbances
  74. Multimodal process monitoring based on variational Bayesian PCA and Kullback-Leibler divergence between mixture models
  75. Valve Stiction Detection and Quantification Using a K-Means Clustering Based Moving Window Approach
  76. Forward–Backward Smoothers With Finite Impulse Response Structure
  77. Hidden Markov Model-Based Attack Detection for Networked Control Systems Subject to Random Packet Dropouts
  78. Stationary Subspace Analysis-Based Hierarchical Model for Batch Processes Monitoring
  79. Data-Driven Fault Detection for Dynamic Systems With Performance Degradation: A Unified Transfer Learning Framework
  80. Dual Neural Extended Kalman Filtering Approach for Multirate Sensor Data Fusion
  81. Kalman Filter-Based Convolutional Neural Network for Robust Tracking of Froth-Middling Interface in a Primary Separation Vessel in Presence of Occlusions
  82. Consensus‐based approach for parameter and state estimation of agro‐hydrological systems
  83. Adjacent-Agent Dynamic Linearization-Based Iterative Learning Formation Control
  84. Discrete-Time Extended State Observer-Based Model-Free Adaptive Control Via Local Dynamic Linearization
  85. Data-Driven Modeling Based on Two-Stream ${\rm{\lambda }}$ Gated Recurrent Unit Network With Soft Sensor Application
  86. Hierarchical Quality-Relevant Feature Representation for Soft Sensor Modeling: A Novel Deep Learning Strategy
  87. Real-Time Mode Diagnosis for Processes With Multiple Operating Conditions Using Switching Conditional Random Fields
  88. Gaussian process regression with heteroscedastic noises — A machine-learning predictive variance approach
  89. Distributed data‐driven observer for linear time invariant systems
  90. Supervised Variational Autoencoders for Soft Sensor Modeling With Missing Data
  91. Detecting the Direction of Information Flow in Instantaneous Relations Between Variables
  92. Iterative Identification of Hammerstein Parameter Varying Systems With Parameter Uncertainties Based on the Variational Bayesian Approach
  93. 3-D Learning-Enhanced Adaptive ILC for Iteration-Varying Formation Tasks
  94. Probabilistic just-in-time approach for nonlinear modeling with Bayesian nonlinear feature extraction
  95. Distributed control performance assessment and corresponding optimal controller design considering communication delays
  96. Neighborhood Variational Bayesian Multivariate Analysis for Distributed Process Monitoring With Missing Data
  97. Feature Extraction of Constrained Dynamic Latent Variables
  98. Simultaneous Static and Dynamic Analysis for Fine-Scale Identification of Process Operation Statuses
  99. Review and Perspectives of Data-Driven Distributed Monitoring for Industrial Plant-Wide Processes
  100. Variational Bayesian Approach for Causality and Contemporaneous Correlation Features Inference in Industrial Process Data
  101. A new soft-sensor algorithm with concurrent consideration of slowness and quality interpretation for dynamic chemical process
  102. Robust filter design for asymmetric measurement noise using variational Bayesian inference
  103. Parameter estimation of Markov-switching Hammerstein systems using variational Bayesian approach
  104. An Improved Data-Driven Point-to-Point ILC Using Additional On-Line Control Inputs With Experimental Verification
  105. Data rectification for multiple operating modes: A MAP framework
  106. Multiple-Model State Estimation Based on Variational Bayesian Inference
  107. Mixtures of Probabilistic PCA With Common Structure Latent Bases for Process Monitoring
  108. Probabilistic Monitoring of Sensors in State-Space With Variational Bayesian Inference
  109. Hierarchically Distributed Monitoring for the Early Prediction of Gas Flare Events
  110. Distributed multiple step ahead prediction considering communication delays
  111. Robust FIR State Estimation of Dynamic Processes Corrupted by Outliers
  112. Deep Discriminative Representation Learning for Nonlinear Process Fault Detection
  113. Semi‐supervised dynamic latent variable modeling: I/O probabilistic slow feature analysis approach
  114. Computationally Efficient Data-Driven Higher Order Optimal Iterative Learning Control
  115. Multivariate Gaussian process regression for nonlinear modelling with colored noise
  116. Chance-Constrained Model Predictive Control for SAGD Process Using Robust Optimization Approximation
  117. An Augmented Model Approach for Identification of Nonlinear Errors-in-Variables Systems Using the EM Algorithm
  118. Recursive Slow Feature Analysis for Adaptive Monitoring of Industrial Processes
  119. Distributed Dynamic Modeling and Monitoring for Large-Scale Industrial Processes under Closed-Loop Control
  120. Control Performance Assessment for ILC-Controlled Batch Processes in a 2-D System Framework
  121. Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE
  122. Approaches to robust process identification: A review and tutorial of probabilistic methods
  123. Localization of Indoor Mobile Robot Using Minimum Variance Unbiased FIR Filter
  124. Distributed Student's t filtering algorithm for heavy-tailed noises
  125. Robust Estimation of ARX Models With Time Varying Time Delays Using Variational Bayesian Approach
  126. Minimum Variance Bound and Minimum Variance Controller for Convex Nonlinear Systems with Input Constraints
  127. Extracting dynamic features with switching models for process data analytics and application in soft sensing
  128. Triggered Communication in Distributed Adaptive High-Gain EKF
  129. A full-condition monitoring method for nonstationary dynamic chemical processes with cointegration and slow feature analysis
  130. Molecular-Based Bayesian Regression Model of Petroleum Fractions
  131. Expectation Maximization Approach for Simultaneous Gross Error Detection and Data Reconciliation Using Gaussian Mixture Distribution
  132. Robust Identification of Nonlinear Errors-in-Variables Systems With Parameter Uncertainties Using Variational Bayesian Approach
  133. Iteration Tuning of Disturbance Observer-Based Control System Satisfying Robustness Index for FOPTD Processes
  134. Nonlinear robust optimization for process design
  135. Detection and Diagnosis of Multiple Faults With Uncertain Modeling Parameters
  136. Interaction Analysis of Multivariate Control Systems Under Bayesian Framework
  137. Bayesian Learning for Dynamic Feature Extraction With Application in Soft Sensing
  138. An E-HOIM Based Data-Driven Adaptive TILC of Nonlinear Discrete-Time Systems for Non-Repetitive Terminal Point Tracking
  139. Mixture semisupervised probabilistic principal component regression model with missing inputs
  140. Computationally-Light Non-Lifted Data-Driven Norm-Optimal Iterative Learning Control
  141. Data-driven high-order terminal iterative learning control with a faster convergence speed
  142. Distributed adaptive high-gain extended Kalman filtering for nonlinear systems
  143. A Probabilistic Just-in-Time Learning Framework for Soft Sensor Development With Missing Data
  144. Semisupervised JITL Framework for Nonlinear Industrial Soft Sensing Based on Locally Semisupervised Weighted PCR
  145. Wavelet Transform Based Methodology for Detection and Characterization of Multiple Oscillations in Nonstationary Variables
  146. Adaptive soft sensor based on time difference Gaussian process regression with local time-delay reconstruction
  147. Distributed monitoring for large-scale processes based on multivariate statistical analysis and Bayesian method
  148. JITL based MWGPR soft sensor for multi-mode process with dual-updating strategy
  149. New results on the robust stability of PID controllers with gain and phase margins for UFOPTD processes
  150. Slow feature analysis for monitoring and diagnosis of control performance
  151. Dynamic higher-order cumulants analysis for state monitoring based on a novel lag selection
  152. Robust Diagnosis of Operating Mode Based on Time-Varying Hidden Markov Models
  153. Robust optimization under correlated uncertainty: Formulations and computational study
  154. Hellinger distance based probability distribution approach to performance monitoring of nonlinear control systems
  155. Predicting wellbore dynamics in a steam-assisted gravity drainage system: Numeric and semi-analytic model, and validation
  156. Generalized expectation–maximization approach to LPV process identification with randomly missing output data
  157. Optimal continuous-time state estimation for linear finite and infinite-dimensional chemical process systems with state constraints
  158. Process monitoring using kernel density estimation and Bayesian networking with an industrial case study
  159. Fault Detection and Diagnosis of Multiple-Model Systems With Mismodeled Transition Probabilities
  160. State estimation incorporating infrequent, delayed and integral measurements
  161. Probabilistic slow feature analysis-based representation learning from massive process data for soft sensor modeling
  162. Diagnosis of Oscillations Between Controller Tuning and Harmonic External Disturbances
  163. A unified data-driven design framework of optimality-based generalized iterative learning control
  164. Bayesian method for simultaneous gross error detection and data reconciliation
  165. Analysis of inter-/intra-E-plate repeatability in the real-time cell analyzer
  166. High-throughput screening assay for the environmental water samples using cellular response profiles
  167. A Bayesian sparse reconstruction method for fault detection and isolation
  168. Minimum variance unbiased FIR filter for discrete time-variant systems
  169. Process monitoring based on factor analysis: Probabilistic analysis of monitoring statistics in presence of both complete and incomplete measurements
  170. Expectation–Maximization Approach to Fault Diagnosis With Missing Data
  171. Detecting and isolating abrupt changes in linear switching systems
  172. Bias-eliminated subspace model identification under time-varying deterministic type load disturbance
  173. State Estimation in Batch Process Based on Two-Dimensional State-Space Model
  174. Multi-input–Multi-output (MIMO) Control System Performance Monitoring Based on Dissimilarity Analysis
  175. A Bayesian framework for real-time identification of locally weighted partial least squares
  176. Operating condition diagnosis based on HMM with adaptive transition probabilities in presence of missing observations
  177. Development of soft sensor by incorporating the delayed infrequent and irregular measurements
  178. Frequency analysis and compensation of valve stiction in cascade control loops
  179. A unified recursive just-in-time approach with industrial near infrared spectroscopy application
  180. Performance Assessment of Industrial Linear Controllers in Univariate Control Loops for Both Set Point Tracking and Load Disturbance Rejection
  181. Nonlinear semisupervised principal component regression for soft sensor modeling and its mixture form
  182. Recursive constrained state estimation using modified extended Kalman filter
  183. Automatic Detection and Frequency Estimation of Oscillatory Variables in the Presence of Multiple Oscillations
  184. Mode of action classification of chemicals using multi-concentration time-dependent cellular response profiles
  185. Inequality constrained parameter estimation using filtering approaches
  186. Constrained particle filtering methods for state estimation of nonlinear process
  187. Bayesian Control Loop Diagnosis by Combining Historical Data and Process Knowledge of Fault Signatures
  188. In vitro cytotoxicity assessment based on KC50 with real-time cell analyzer (RTCA) assay
  189. Design of inferential sensors in the process industry: A review of Bayesian methods
  190. Moving horizon estimation for switching nonlinear systems
  191. Parameter estimation in batch process using EM algorithm with particle filter
  192. Soft sensors for online steam quality measurements of OTSGs
  193. FIR model identification of multirate processes with random delays using EM algorithm
  194. A moving horizon approach to a noncontinuum state estimation
  195. Soft sensor solutions for control of oil sands processes
  196. Control loop diagnosis with ambiguous historical operating modes: Part 1. A proportional parametrization approach
  197. Cytotoxicity assessment based on the AUC50 using multi-concentration time-dependent cellular response curves
  198. Compensation of control valve stiction through controller tuning
  199. 4th Symposium on advanced control of industrial processes (Adconip)
  200. Guest Editorial: 4TH symposium on advanced control of industrial processes (ADCONIP)
  201. Deterministic vs. stochastic performance assessment of iterative learning control for batch processes
  202. Microelectronic-sensing assay to detect presence of Verotoxins in human faecal samples
  203. Dual particle filters for state and parameter estimation with application to a run-of-mine ore mill
  204. Tuning a Soft Sensor’s Bias Update Term. 1. The Open-Loop Case
  205. Estimation of bitumen froth quality using Bayesian information synthesis: An application to froth transportation process
  206. Identification of nonlinear parameter varying systems with missing output data
  207. Designing priors for robust Bayesian optimal experimental design
  208. Multiple model based LPV soft sensor development with irregular/missing process output measurement
  209. Prediction error method for identification of LPV models
  210. Dynamic output feedback robust model predictive control
  211. Estimation of distribution function for control valve stiction estimation
  212. Performance assessment of PID control loops subject to setpoint changes
  213. Closed-loop identification with routine operating data: Effect of time delay and sampling time
  214. Bayesian methods for control loop diagnosis in the presence of temporal dependent evidences
  215. Data-based modeling and prediction of cytotoxicity induced by contaminants in water resources
  216. Reconciling continuum and non-continuum data with industrial application
  217. Monitoring of solid oxide fuel cell systems
  218. A decoupled multiple model approach for soft sensors design
  219. Constrained receding-horizon experiment design and parameter estimation in the presence of poor initial conditions
  220. Subspace Approach to Identification of Step-Response Model from Closed-Loop Data
  221. Performance assessment of advanced supervisory–regulatory control systems with subspace LQG benchmark
  222. Dynamic Bayesian Approach for Control Loop Diagnosis with Underlying Mode Dependency
  223. The DCT-based oscillation detection method for a single time series
  224. Estimation and control of solid oxide fuel cell system
  225. Multi-step prediction error approach for controller performance monitoring
  226. Stiction Estimation Using Constrained Optimisation and Contour Map
  227. Consistency of noise covariance estimation in joint input–output closed-loop subspace identification with application in LQG benchmarking
  228. Subspace method aided data-driven design of fault detection and isolation systems
  229. H∞structured model reduction algorithms for linear discrete systems via LMI-based optimisation
  230. Identification of Hammerstein systems without explicit parameterisation of non-linearity
  231. Closed-loop model validation based on the two-model divergence method
  232. MPC Constraint Analysis—Bayesian Approach via a Continuous-Valued Profit Function
  233. Preferential crystallization: Multi-objective optimization framework
  234. Validation of continuous-time models with delay
  235. A Bayesian approach for control loop diagnosis with missing data
  236. Dealing with Irregular Data in Soft Sensors: Bayesian Method and Comparative Study
  237. Bayesian methods for control loop monitoring and diagnosis
  238. Robust H2 optimal filtering for con...
  239. Sensitivity analysis for selective constraint and variability tuning in performance assessment of industrial MPC
  240. Control relevant on-line model validation criterion based on robust stability conditions
  241. Performance assessment of MIMO control systems with time-variant disturbance dynamics
  242. Reformulation of LMI-based stabilisation conditions for non-linear systems in Takagi–Sugeno's form
  243. Identification from step responses with transient initial conditions
  244. 1-D dynamic modeling of SOFC with analytical solution for reacting gas-flow problem
  245. Dynamics and variance control of hot mill loopers
  246. Assessing Model Prediction Control (MPC) Performance. 1. Probabilistic Approach for Constraint Analysis
  247. Output feedback model predictive control for nonlinear systems represented by Hammerstein–Wiener model
  248. New formulation of robust MPC by incorporating off-line approach with on-line optimization
  249. Comments on "A Feedback Min-Max MPC Algorithm for LPV Systems Subject to Bounded Rates of Change of Parameters
  250. Constrained robust model predictive control for time-delay systems with polytopic description
  251. A blind approach to closed-loop identification of Hammerstein systems
  252. Data-driven predictive control for solid oxide fuel cells
  253. Improved identification of continuous-time delay processes from piecewise step tests
  254. Monitoring control performance via structured closed-loop response subject to output variance/covariance upper bound
  255. Dynamic modeling of a finite volume of solid oxide fuel cell: The effect of transport dynamics
  256. Performance monitoring of SISO control loops subject to LTV disturbance dynamics: An improved LTI benchmark
  257. Alternative solutions to multi-variate control performance assessment problems
  258. A new method for stabilization of networked control systems with random delays
  259. Multirate robust digital control for fuzzy systems with periodic Lyapunov function
  260. Practical solutions to multivariate feedback control performance assessment problem: reduced a priori knowledge of interactor matrices
  261. Closed-loop subspace identification: an orthogonal projection approach
  262. Fixed-order controller design for linear time-invariant descriptor systems: A BMI approach
  263. Performance assessment and robustness analysis using an ARMarkov approach
  264. Robust Model Predictive Control of Singular Systems
  265. Feedforward and Feedback Controller Performance Assessment of Linear Time-Variant Processes
  266. Industrial Applications of a Feedback Controller Performance Assessment of Time-Variant Processes
  267. Performance evaluation of two industrial MPC controllers
  268. H∞ model reduction of Markovian jump linear systems
  269. LMI synthesis of H/sup 2/ and mixed H/sub 2//H/sub ∞/ controllers for singular systems
  270. Model predictive control relevant identification and validation
  271. Improved Threshold for the Local Approach in Detecting Faults
  272. A pragmatic approach towards assessment of control loop performance
  273. Controller performance assessment in set point tracking and regulatory control
  274. On gramians and balanced truncation of discrete-time bilinear systems
  275. Estimation of the Dynamic Matrix and Noise Model for Model Predictive Control Using Closed-Loop Data