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[1]ADP-Based Event-Triggered Constrained Optimal Control on Spatiotemporal Process: Application to Temperature Field in Roller Kiln.IEEE Transactions on Neural Networks and Learning Systems, 2023
[2]A Multi-particle Cellular Automaton Modeling Method for Grain Dynamics Evolution of Nickel-rich Cathode Material.Materials Today Energy, 2023, 35
[3]Event-Triggered Optimal Control for Temperature Field of Roller Kiln Based on Adaptive Dynamic Programming.IEEE Transactions on Cybernetics, 2022
[4]基于参数估计误差的辊道窑温度场优化控制方法.控制理论与应用, 2022
[5]Hybrid Modeling and Distributed Optimization Control Method for the Iron Removal Process.Journal of Industrial and Management Optimization, 2022
[6]Design of a Non-Linear Observer for SOC of Lithium-Ion Battery Based on Neural Network.Energies, 2022, 15 (10) : 3835.
[7]A Process Monitoring Method Based on Dynamic Autoregressive Latent Variable Model and Its Application in the Sintering Process of Ternary Cathode Materials.Machines, 2021, 9 (10) : 229.
[8]A goethite process modeling method by asynchronous fuzzy cognitive network based on an improved constrained chicken swarm optimization algorithm.Journal of Industrial & Management Optimization, 2021, 17 (3) : 1269-1287.
[9]A hybrid model combining mechanism with semi-supervised learning and its application for temperature prediction in roller hearth kiln.Journal of Process Control, 2021, 98: 18-29.
[10]Multi-scale local LSSVM based spatiotemporal modeling and optimal control for the goethite process.Neurocomputing, 2020, 385: 88–99.
[11]Estimating the state-of-charge of lithium-ion battery using an H-infinity observer based on electrochemical impedance model.IEEE Access, 2020, 8: 26872-26884.
[12]An ensemble just-in-time learning soft-sensor model for residual lithium concentration prediction of ternary cathode materials.Journal of Chemometrics, 2020, 34: e3225.
[13]Optimal Control of Iron-Removal Systems Based on Off-Policy Reinforcement Learning.IEEE Access, 2020, 8: 149730-149740.
[14]A hybrid prediction model with a selectively updating strategy for iron removal process in zinc hydrometallurgy.Science China Information Sciences, 2020, 63 (1) : 119205.
[15]Temperature prediction for roller kiln based on hybrid first-principle model and data-driven MW-DLWKPCR model.ISA Transactions, 2020, 98: 403-417.
[16]Modeling of goethite iron precipitation process based on T-GFCN.Journal of Central South University, 2019, 26: 63-74.
[17]Distributed model predictive control of iron precipitation process by goethite based on dual iterative method.International Journal of Control Automation and Systems, 2019, 17 (5) : 1233-1245.
[18]Time-varying bang-bang property of time optimal controls for heat equation and its application.System & Control letters, 2018, 112 (1) : 18-23.
[19]Time-varying bang-bang property of time optimal controls for heat equation and its application.System & Control letters, 2018, 112 (1) : 18-23.
[20]Temperature Prediction Model for Roller Kiln by ALD-Based Double Locally Weighted Kernel Principal Component Regression.IEEE Transactions on Instrumentation and measurement, 2018, 67 (8) : 2001-2010.
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