Hybrid Intelligent System for Supervisory Control of Mineral Grinding Process. - Jinliang Ding; Ping Zhou 003; Changxin Liu 003; Tianyou Chai (ISDA (1), 2006)

An intelligent approach for supervisory control of grinding product particle size. - Ping Zhou 003; Jinliang Ding; Tianyou Chai; Hong Wang 001; Chun-Yi Su (CDC, 2007)

Multivariable decoupling internal model control for grinding circuit. - Ping Zhou 003; Tianyou Chai; Hong Wang 001; Chun-Yi Su (ACC, 2008)

Frequency-domain weighted RLS model reduction for complex SISO linear system. - Ping Zhou 003; Tianyou Chai; Qiang Liu 018; Hong Wang 001; Chun-Yi Su (ACC, 2009)

Intelligent Optimal-Setting Control for Grinding Circuits of Mineral Processing Process. - Ping Zhou 003; Tianyou Chai; Hong Wang 001 (IEEE Trans Autom. Sci. Eng., 2009)

DOB Design for Nonminimum-Phase Delay Systems and Its Application in Multivariable MPC Control. - Ping Zhou 003; Tianyou Chai; Jin-Hui Zhao (IEEE Trans. Circuits Syst. II Express Briefs, 2012)

Intelligence-Based Supervisory Control for Optimal Operation of a DCS-Controlled Grinding System. - Ping Zhou 003; Tianyou Chai; Jing Sun 003 (IEEE Trans. Control. Syst. Technol., 2013)

Modeling and Simulation of Whole Ball Mill Grinding Plant for Integrated Control. - Shaowen Lu; Ping Zhou 003; Tianyou Chai; Wei Dai 004 (IEEE Trans Autom. Sci. Eng., 2014)

Data-Driven Soft-Sensor Modeling for Product Quality Estimation Using Case-Based Reasoning and Fuzzy-Similarity Rough Sets. - Ping Zhou 003; Shaowen Lu; Tianyou Chai (IEEE Trans Autom. Sci. Eng., 2014)

Multivariable Disturbance Observer Based Advanced Feedback Control Design and Its Application to a Grinding Circuit. - Ping Zhou 003; Wei Dai 004; Tianyou Chai (IEEE Trans. Control. Syst. Technol., 2014)

Multivariable dynamic modeling for molten iron quality using online sequential random vector functional-link networks with self-feedback connections. - Ping Zhou 003; Meng Yuan; Hong Wang 001; Zhuo Wang 003; Tianyou Chai (Inf. Sci., 2015)

Modeling for output fiber length distribution of refining process using wavelet neural networks trained by NSGA II and gradient based two-stage hybrid algorithm. - Ping Zhou 003; Mingjie Li 001; Dongwei Guo; Hong Wang 001; Tianyou Chai (Neurocomputing, 2017)

Parametric design-based multi-objective optimisation for high-pressure turbine disc. - Dongliang Cui; Guoqi Feng; Ping Zhou 003; Yajun Zhang (Int. J. Prod. Res., 2017)

Data-Driven Nonlinear Subspace Modeling for Prediction and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking. - Ping Zhou 003; Heda Song; Hong Wang 001; Tianyou Chai (IEEE Trans. Control. Syst. Technol., 2017)

Data-Driven Robust RVFLNs Modeling of a Blast Furnace Iron-Making Process Using Cauchy Distribution Weighted M-Estimation. - Ping Zhou 003; Youbin Lv; Hong Wang 001; Tianyou Chai (IEEE Trans. Ind. Electron., 2017)

Model Free Adaptive Predictive Control of Multivariate Molten Iron Quality in Blast Furnace Ironmaking. - Liang Wen; Ping Zhou 003; Hong Wang 001; Tianyou Chai (CDC, 2018)

Data-driven predictive control of molten iron quality in blast furnace ironmaking using multi-output LS-SVR based inverse system identification. - Ping Zhou 003; Dongwei Guo; Tianyou Chai (Neurocomputing, 2018)

Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking. - Ping Zhou 003; Chenyu Wang; Mingjie Li 001; Hong Wang 001; Yongjian Wu; Tianyou Chai (Neurocomputing, 2018)

EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems. - Yuyang Zhou; Qichun Zhang; Hong Wang 001; Ping Zhou 003; Tianyou Chai (IEEE Trans. Autom. Control., 2018)

Data-Driven Robust M-LS-SVR-Based NARX Modeling for Estimation and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking. - Ping Zhou 003; Dongwei Guo; Hong Wang 001; Tianyou Chai (IEEE Trans. Neural Networks Learn. Syst., 2018)

Data modeling for quality prediction using improved orthogonal incremental random vector functional-link networks. - Ping Zhou 003; Yue Jiang; Chaoyao Wen; Tianyou Chai (Neurocomputing, 2019)

Stochastic configuration networks with block increments for data modeling in process industries. - Wei Dai 004; Depeng Li 001; Ping Zhou 003; Tianyou Chai (Inf. Sci., 2019)

Geometric Analysis Based Double Closed-Loop Iterative Learning Control of Output PDF Shaping of Fiber Length Distribution in Refining Process. - Mingjie Li 001; Ping Zhou 003; Hong Wang 001; Tianyou Chai (IEEE Trans. Ind. Electron., 2019)

Multi-model based PSO method for burden distribution matrix optimization with expected burden distribution output behaviors. - Yong Zhang 008; Ping Zhou 003; Guimei Cui (IEEE CAA J. Autom. Sinica, 2019)

Recursive Learning-Based Bilinear Subspace Identification for Online Modeling and Predictive Control of a Complicated Industrial Process. - Ping Zhou 003; Shuai Zhang; Peng Dai (IEEE Access, 2020)

Dynamic performance enhancement for nonlinear stochastic systems using RBF driven nonlinear compensation with extended Kalman filter. - Yuyang Zhou; Aiping Wang; Ping Zhou 003; Hong Wang 001; Tianyou Chai (Autom., 2020)

Robust stochastic configuration network multi-output modeling of molten iron quality in blast furnace ironmaking. - Jin Xie; Ping Zhou 003 (Neurocomputing, 2020)

Data-Driven Predictive Probability Density Function Control of Fiber Length Stochastic Distribution Shaping in Refining Process. - Mingjie Li 001; Ping Zhou 003; Yunlong Liu; Hong Wang 001 (IEEE Trans Autom. Sci. Eng., 2020)

Distributed Robust Event-Triggered Control Strategy for Multiple High-Speed Trains With Communication Delays and Input Constraints. - Hui Zhao 017; Xuewu Dai; Ping Zhou 003; Tao Yang 003 (IEEE Trans. Control. Netw. Syst., 2020)

Robust Online Sequential RVFLNs for Data Modeling of Dynamic Time-Varying Systems With Application of an Ironmaking Blast Furnace. - Ping Zhou 003; Wenpeng Li; Hong Wang 001; Mingjie Li 001; Tianyou Chai (IEEE Trans. Cybern., 2020)

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking. - Mingjie Li 001; Ping Zhou 003; Hong Wang 001; Tianyou Chai (IEEE Trans. Syst. Man Cybern. Syst., 2020)

Fast just-in-time-learning recursive multi-output LSSVR for quality prediction and control of multivariable dynamic systems. - Ping Zhou 003; Weiqi Chen; Chengming Yi; Zhaohui Jiang; Tao Yang 003; Tianyou Chai (Eng. Appl. Artif. Intell., 2021)

Data-Driven Monitoring and Diagnosing of Abnormal Furnace Conditions in Blast Furnace Ironmaking: An Integrated PCA-ICA Method. - Ping Zhou 003; Ruiyao Zhang; Jin Xie; Jiping Liu; Hong Wang 001; Tianyou Chai (IEEE Trans. Ind. Electron., 2021)

Improved Incremental RVFL With Compact Structure and Its Application in Quality Prediction of Blast Furnace. - Ping Zhou 003; Yue Jiang; Chaoyao Wen; Xuewu Dai (IEEE Trans. Ind. Informatics, 2021)

Data-Driven Multiobjective Predictive Optimal Control of Refining Process With Non-Gaussian Stochastic Distribution Dynamics. - Mingjie Li 001; Ping Zhou 003; Liangyong Wang; Ye Yuan 001 (IEEE Trans. Ind. Informatics, 2021)

Intelligent Prediction of Train Delay Changes and Propagation Using RVFLNs With Improved Transfer Learning and Ensemble Learning. - Ping Zhou 003; Lefang Chen; Xuewu Dai; Baoxu Li; Tianyou Chai (IEEE Trans. Intell. Transp. Syst., 2021)

Incremental learning paradigm with privileged information for random vector functional-link networks: IRVFL+. - Wei Dai 004; Yanshuang Ao; Linna Zhou; Ping Zhou 003; Xuesong Wang 001 (Neural Comput. Appl., 2022)

Kalman Filter-Based Data-Driven Robust Model-Free Adaptive Predictive Control of a Complicated Industrial Process. - Ping Zhou 003; Shuai Zhang; Liang Wen; Jun Fu 001; Tianyou Chai; Hong Wang 001 (IEEE Trans Autom. Sci. Eng., 2022)

Identification of Abnormal Conditions for Fused Magnesium Melting Process Based on Deep Learning and Multisource Information Fusion. - Ping Zhou 003; Benhua Gao; Shu Wang; Tianyou Chai (IEEE Trans. Ind. Electron., 2022)

Compact Incremental Random Weight Network for Estimating the Underground Airflow Quantity. - Qianjin Wang; Wei Dai 004; Ping Lin; Ping Zhou 003 (IEEE Trans. Ind. Informatics, 2022)

Inverse Calculation of Burden Distribution Matrix Using B-Spline Model Based PDF Control in Blast Furnace Burden Charging Process. - Yong Zhang 008; Ping Zhou 003; Donghao Lv; Sen Zhang 001; Guimei Cui; Hong Wang 001 (IEEE Trans. Ind. Informatics, 2023)

SPEA2 based on grid density search and elite guidance for multi-objective operation optimization of wastewater treatment process. - Ping Zhou 003; Hongpeng Li; Tianyou Chai (Appl. Soft Comput., 2023)

Enhanced NMPC for Stochastic Dynamic Systems Driven by Control Error Compensation With Entropy Optimization. - Ping Zhou 003; Xiaoyang Sun; Tianyou Chai (IEEE Trans. Control. Syst. Technol., 2023)

Multiobjective Operation Optimization of Wastewater Treatment Process Based on Reinforcement Self-Learning and Knowledge Guidance. - Ping Zhou 003; Xuan Wang; Tianyou Chai (IEEE Trans. Cybern., 2023)

Anomaly Detection of Nonstationary Long-Memory Processes Based on Fractional Cointegration Vector Autoregression. - Ruiyao Zhang; Ping Zhou 003; Junfei Qiao 001 (IEEE Trans. Reliab., 2023)

Anomaly Detection of Industrial Smelting Furnace Incorporated With Accelerated Sampling Denoising Diffusion Probability Model and Conv-Transformer. - Yu Zhang 232; Ping Zhou 003; Enjie Ma (IEEE Trans. Instrum. Meas., 2024)

Objective PDF-Shaping Based Stochastic Optimization With Probabilistic Constraints and Its Application. - Mingjie Li 001; Ping Zhou 003; Hong Wang 001 (IEEE Trans. Ind. Electron., 2024)

Online Sequential Sparse Robust Neural Networks With Random Weights for Imperfect Industrial Streaming Data Modeling. - Chaoyao Wen; Ping Zhou 003; Wei Dai 004; Liang Dong; Tianyou Chai (IEEE Trans Autom. Sci. Eng., 2024)

Guest Editorial Special Issue on Learning From Imperfect Data for Industrial Automation. - Ping Zhou 003; Xuewu Dai; Kyriakos G. Vamvoudakis; Jan Faigl; Hong Wang 001 (IEEE Trans Autom. Sci. Eng., 2024)

Adaptive Constraint Penalty-Based Multiobjective Operation Optimization of an Industrial Dynamic System With Complex Multiconstraint. - Ping Zhou 003; Shuai Zhang; Tianyou Chai (IEEE Trans. Cybern., 2024)

Optimal Tracking Control of Blast Furnace Molten Iron Quality Based on Krotov's Method and Nonlinear Subspace Identification. - Yue Liu; Ping Zhou 003; Xiaoyang Sun; Tianyou Chai (IEEE Trans. Ind. Electron., 2024)

An Interpretable Constructive Algorithm for Incremental Random Weight Neural Networks and Its Application. - Jing Nan; Wei Dai 004; Guan Yuan; Ping Zhou 003 (IEEE Trans. Ind. Informatics, 2024)

Ironmaking process modeling uncertainty quantification via conformal prediction based on random vector functional link networks. - Ping Zhou 003; Chaoyao Wen; Peng Zhao; Mingjie Li 001 (Comput. Electr. Eng., 2025)

Virtual Error-Based Data-Driven P-Type Adaptive Predictive Control and Its Applications. - Guojie Li; Ping Zhou 003; Yuyang Zhou; Tianyou Chai (IEEE Trans Autom. Sci. Eng., 2025)

Intelligent Working Conditions Recognition Method and Application Incorporating Semi-Supervised Learning With Multilevel Information Fusion. - Ping Zhou 003; Benyi Jiang; Yu Zhang 232; Tianyou Chai (IEEE Trans. Instrum. Meas., 2025)

Intelligent recognition of steel plate surface defect based on deep convolutional GAN. - Benyi Jiang; Ping Zhou 003; Xiaoyang Sun; Tianyou Chai (Neural Comput. Appl., 2025)

Uncertainty Quantification Based on Conformal Prediction for Industrial Time Series With Distribution Shift. - Ruiyao Zhang; Ping Zhou 003 (IEEE Trans. Ind. Informatics, 2025)

Stacked semi-supervised autoencoder-regularized RVFLNs for reliable prediction of molten iron quality in blast furnace. - Ping Zhou 003; Peng Zhao; Zihui Ou; Tianyou Chai (Neural Comput. Appl., 2025)