Ping Zhou
Orcid: 0000-0002-9398-172XAffiliations:
- Northeastern University, State Key Laboratory of Synthetical Automation for Process Industries, Shenyang, China (PhD 2013)
According to our database1,
Ping Zhou
authored at least 49 papers
between 2006 and 2024.
Collaborative distances:
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Bibliography
2024
Guest Editorial Special Issue on Learning From Imperfect Data for Industrial Automation.
IEEE Trans Autom. Sci. Eng., April, 2024
Online Sequential Sparse Robust Neural Networks With Random Weights for Imperfect Industrial Streaming Data Modeling.
IEEE Trans Autom. Sci. Eng., April, 2024
Objective PDF-Shaping Based Stochastic Optimization With Probabilistic Constraints and Its Application.
IEEE Trans. Ind. Electron., March, 2024
Anomaly Detection of Industrial Smelting Furnace Incorporated With Accelerated Sampling Denoising Diffusion Probability Model and Conv-Transformer.
IEEE Trans. Instrum. Meas., 2024
2023
Anomaly Detection of Nonstationary Long-Memory Processes Based on Fractional Cointegration Vector Autoregression.
IEEE Trans. Reliab., December, 2023
Multiobjective Operation Optimization of Wastewater Treatment Process Based on Reinforcement Self-Learning and Knowledge Guidance.
IEEE Trans. Cybern., November, 2023
Enhanced NMPC for Stochastic Dynamic Systems Driven by Control Error Compensation With Entropy Optimization.
IEEE Trans. Control. Syst. Technol., September, 2023
SPEA2 based on grid density search and elite guidance for multi-objective operation optimization of wastewater treatment process.
Appl. Soft Comput., September, 2023
Inverse Calculation of Burden Distribution Matrix Using B-Spline Model Based PDF Control in Blast Furnace Burden Charging Process.
IEEE Trans. Ind. Informatics, 2023
An Interpretable Constructive Algorithm for Incremental Random Weight Neural Networks and Its Application.
CoRR, 2023
2022
Compact Incremental Random Weight Network for Estimating the Underground Airflow Quantity.
IEEE Trans. Ind. Informatics, 2022
Identification of Abnormal Conditions for Fused Magnesium Melting Process Based on Deep Learning and Multisource Information Fusion.
IEEE Trans. Ind. Electron., 2022
Kalman Filter-Based Data-Driven Robust Model-Free Adaptive Predictive Control of a Complicated Industrial Process.
IEEE Trans Autom. Sci. Eng., 2022
Incremental learning paradigm with privileged information for random vector functional-link networks: IRVFL+.
Neural Comput. Appl., 2022
2021
Intelligent Prediction of Train Delay Changes and Propagation Using RVFLNs With Improved Transfer Learning and Ensemble Learning.
IEEE Trans. Intell. Transp. Syst., 2021
Data-Driven Multiobjective Predictive Optimal Control of Refining Process With Non-Gaussian Stochastic Distribution Dynamics.
IEEE Trans. Ind. Informatics, 2021
Improved Incremental RVFL With Compact Structure and Its Application in Quality Prediction of Blast Furnace.
IEEE Trans. Ind. Informatics, 2021
Data-Driven Monitoring and Diagnosing of Abnormal Furnace Conditions in Blast Furnace Ironmaking: An Integrated PCA-ICA Method.
IEEE Trans. Ind. Electron., 2021
Fast just-in-time-learning recursive multi-output LSSVR for quality prediction and control of multivariable dynamic systems.
Eng. Appl. Artif. Intell., 2021
2020
Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking.
IEEE Trans. Syst. Man Cybern. Syst., 2020
Robust Online Sequential RVFLNs for Data Modeling of Dynamic Time-Varying Systems With Application of an Ironmaking Blast Furnace.
IEEE Trans. Cybern., 2020
Distributed Robust Event-Triggered Control Strategy for Multiple High-Speed Trains With Communication Delays and Input Constraints.
IEEE Trans. Control. Netw. Syst., 2020
Data-Driven Predictive Probability Density Function Control of Fiber Length Stochastic Distribution Shaping in Refining Process.
IEEE Trans Autom. Sci. Eng., 2020
Robust stochastic configuration network multi-output modeling of molten iron quality in blast furnace ironmaking.
Neurocomputing, 2020
Dynamic performance enhancement for nonlinear stochastic systems using RBF driven nonlinear compensation with extended Kalman filter.
Autom., 2020
Recursive Learning-Based Bilinear Subspace Identification for Online Modeling and Predictive Control of a Complicated Industrial Process.
IEEE Access, 2020
2019
Geometric Analysis Based Double Closed-Loop Iterative Learning Control of Output PDF Shaping of Fiber Length Distribution in Refining Process.
IEEE Trans. Ind. Electron., 2019
Stochastic configuration networks with block increments for data modeling in process industries.
Inf. Sci., 2019
Data modeling for quality prediction using improved orthogonal incremental random vector functional-link networks.
Neurocomputing, 2019
2018
Data-Driven Robust M-LS-SVR-Based NARX Modeling for Estimation and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking.
IEEE Trans. Neural Networks Learn. Syst., 2018
IEEE Trans. Autom. Control., 2018
Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking.
Neurocomputing, 2018
Data-driven predictive control of molten iron quality in blast furnace ironmaking using multi-output LS-SVR based inverse system identification.
Neurocomputing, 2018
Model Free Adaptive Predictive Control of Multivariate Molten Iron Quality in Blast Furnace Ironmaking.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
2017
Data-Driven Robust RVFLNs Modeling of a Blast Furnace Iron-Making Process Using Cauchy Distribution Weighted M-Estimation.
IEEE Trans. Ind. Electron., 2017
Data-Driven Nonlinear Subspace Modeling for Prediction and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking.
IEEE Trans. Control. Syst. Technol., 2017
Int. J. Prod. Res., 2017
Modeling for output fiber length distribution of refining process using wavelet neural networks trained by NSGA II and gradient based two-stage hybrid algorithm.
Neurocomputing, 2017
2015
Multivariable dynamic modeling for molten iron quality using online sequential random vector functional-link networks with self-feedback connections.
Inf. Sci., 2015
2014
Multivariable Disturbance Observer Based Advanced Feedback Control Design and Its Application to a Grinding Circuit.
IEEE Trans. Control. Syst. Technol., 2014
Data-Driven Soft-Sensor Modeling for Product Quality Estimation Using Case-Based Reasoning and Fuzzy-Similarity Rough Sets.
IEEE Trans Autom. Sci. Eng., 2014
IEEE Trans Autom. Sci. Eng., 2014
2013
Intelligence-Based Supervisory Control for Optimal Operation of a DCS-Controlled Grinding System.
IEEE Trans. Control. Syst. Technol., 2013
2012
DOB Design for Nonminimum-Phase Delay Systems and Its Application in Multivariable MPC Control.
IEEE Trans. Circuits Syst. II Express Briefs, 2012
2009
Intelligent Optimal-Setting Control for Grinding Circuits of Mineral Processing Process.
IEEE Trans Autom. Sci. Eng., 2009
Proceedings of the American Control Conference, 2009
2008
Proceedings of the American Control Conference, 2008
2007
Proceedings of the 46th IEEE Conference on Decision and Control, 2007
2006
Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications (ISDA 2006), 2006