Hao Tian - IEEE Xplore Author Profile

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Author details

Hao Tian

Publications

10

Citations

9

Publications by Year

20232025

Co-Authors:

Canlin CuiXiaotong PanJunfei QiaoJian TangZixuan Wang

Show All Co-Authors (14)

Hao Tian

Affiliation

Faculty of Information Technology

Beijing University of Technology

Beijing, China

Publication Topics

Municipal Solid Waste,
Municipal Solid Waste Incineration,
Furnace Temperature,
Solid Waste,
Fuzzy Neural Network,
Neural Network,
Back Propagation Neural Network,
Learning Rate,
Waste Incineration Processes,
Adaptive Control,
Control Strategy,
Control Variables

Biography

Hao Tian received the B.S. degree in automatic control from Shandong Technology and Business University, Yantai, China, in 2022. He is currently working toward the M.S. degree in control theory and control engineering with Beijing University of Technology, Beijing, China.,His current research interests include intelligent control of furnace temperature in municipal solid waste incineration process.(Based on document published on 24 September 2024).

Publications

10

Citations

9

Publications by Year

20232025

Co-Authors:

Canlin Cui
Xiaotong Pan
Junfei Qiao
Jian Tang
Zixuan Wang

Show All Co-Authors (14)

Author's Published Works

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Showing 1-10 of 10 results

Conferences (9)

Journals (1)

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Heng Xia(10)
Hao Tian(10)
Jian Tang(10)
Tianzheng Wang(7)
Wen Yu(3)
Faculty of Information Technology, Beijing University of Technology, Beijing, China(9)
State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China(3)
Departamento de Control Automatico, CINVESTAV-IPN (National Polytechnic Institute), Mexico City, Mexico(2)
Faculty of Information Technology, Beijing University of Technology Beijing Laboratory of Smart Environmental Protection, Beijing, China(1)
Departamento de Control Automatico, CINVESTAV-IPN, Mexico City, Mexico(1)
2023 35th Chinese Control and Decision Conference (CCDC)(4)
2024 36th Chinese Control and Decision Conference (CCDC)(4)
2024 6th International Conference on Industrial Artificial Intelligence (IAI)(1)
IEEE Transactions on Industrial Informatics(1)
IEEE(10)
Media(1)
Xi'an, China(4)
Yichang, China(4)
Shenyang, China(1)
Municipal Solid Waste(9)
Municipal Solid Waste Incineration(9)
Furnace Temperature(8)
Solid Waste(8)
Fuzzy Neural Network(5)

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Results

Bayesian Optimization-Based Interval Type-2 Fuzzy Neural Network for Furnace Temperature Control

Hao Tian;Jian Tang;Heng Xia;Wen Yu;Junfei Qiao

IEEE Transactions on Industrial Informatics

Year: 2025 | Volume: 21, Issue: 1 | Journal Article |

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The furnace temperature (FT) control is the key for ensuring the stable operation and effective pollution reduction in municipal solid waste incineration (MSWI) processes. However, conventional control strategies encounter challenges in effectively managing FT due to uncertainties associated with material composition, feeding modes, and equipment maintenance. In response to these challenges, this ...Show More

Bayesian Optimization-Based Interval Type-2 Fuzzy Neural Network for Furnace Temperature Control

Hao Tian;Jian Tang;Heng Xia;Wen Yu;Junfei Qiao

IEEE Transactions on Industrial Informatics

Year: 2025 | Volume: 21, Issue: 1 | Journal Article |

Conservative Q-Learning Based Furnace Temperature Control in Municipal Solid Waste Incineration Process

Hao Tian;Jian Tang;Heng Xia;Jian Zhang;Tianzheng Wang;Wen Yu

2024 6th International Conference on Industrial Artificial Intelligence (IAI)

Year: 2024 | Conference Paper |

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The nonlinear, time-varying, and lagging nature of the municipal solid waste incineration (MSWI) process presents challenges for ensuring controller safety. While offline reinforcement learning (RL) can ensure safety in furnace temperature (FT) control, its performance is hindered by extrapolation errors, making it unsuitable for direct application in the incineration environment. To address this,...Show More

Conservative Q-Learning Based Furnace Temperature Control in Municipal Solid Waste Incineration Process

Hao Tian;Jian Tang;Heng Xia;Jian Zhang;Tianzheng Wang;Wen Yu

2024 6th International Conference on Industrial Artificial Intelligence (IAI)

Year: 2024 | Conference Paper |

Interval Type-2 Fuzzy Neural Network Control for Furnace Temperature in Municipal Solid Waste Incineration Processes

Hao Tian;Jian Tang;Heng Xia

2024 36th Chinese Control and Decision Conference (CCDC)

Year: 2024 | Conference Paper |

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Furnace temperature plays a pivotal role in ensuring the stability of municipal solid waste incineration (MSWI), influenced by variable factors such as material composition, feeding patterns, and equipment operation. We introduce an interval type-2 fuzzy neural network (IT2FNN) control method. Initially, we analyze furnace temperature control characteristics to identity crucial operating variables...Show More

Interval Type-2 Fuzzy Neural Network Control for Furnace Temperature in Municipal Solid Waste Incineration Processes

Hao Tian;Jian Tang;Heng Xia

2024 36th Chinese Control and Decision Conference (CCDC)

Year: 2024 | Conference Paper |

An Improved Hierarchical Fused Fuzzy Deep Neural Network Method for Controlled Object Model of Furnace Temperature for MSWI Process

Hao Tian;Jian Tang;Heng Xia;Tianzheng Yang;Aijun Yan;Zhiwei Wu

2024 36th Chinese Control and Decision Conference (CCDC)

Year: 2024 | Conference Paper |

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Addressing the challenge of precisely controlling furnace temperature, this study introduces a modeling strategy based on an enhanced hierarchical fused fuzzy deep neural network (HF-FDNN) model. Initially, an analysis of the control characteristics of furnace temperature identifies key manipulated variables (MVs). Subsequently, we refine the HF-FDNN algorithm within the task-driven layer to devel...Show More

An Improved Hierarchical Fused Fuzzy Deep Neural Network Method for Controlled Object Model of Furnace Temperature for MSWI Process

Hao Tian;Jian Tang;Heng Xia;Tianzheng Yang;Aijun Yan;Zhiwei Wu

2024 36th Chinese Control and Decision Conference (CCDC)

Year: 2024 | Conference Paper |

Adaptive PID Control of Furnace Temperature in MSWI Process Based on Reinforcement Learning

Hao Tian;Jian Tang;Heng Xia;Tianzheng Wang;Wen Yu;Zhiwei Wu

2024 36th Chinese Control and Decision Conference (CCDC)

Year: 2024 | Conference Paper |

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This paper tackles the challenge of effectively regulating furnace temperature in the municipal solid waste incineration (MSWI) process. It proposes an approach that integrates reinforcement learning with traditional PID control. Firstly, an analysis of the characteristics of furnace temperature control is conducted to identify the key manipulated variables affecting it. Subsequently, a control st...Show More

Adaptive PID Control of Furnace Temperature in MSWI Process Based on Reinforcement Learning

Hao Tian;Jian Tang;Heng Xia;Tianzheng Wang;Wen Yu;Zhiwei Wu

2024 36th Chinese Control and Decision Conference (CCDC)

Year: 2024 | Conference Paper |

Furnace Temperature Control for MSWI Process Based on Neural Network Predictive Controller

Bokang Wang;Jian Tang;Heng Xia;Hao Tian;Tianzheng Wang;Zhiwei Wu

2024 36th Chinese Control and Decision Conference (CCDC)

Year: 2024 | Conference Paper |

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To tackle the challenge of controlling furnace temperature in municipal solid waste incineration (MSWI), which is critical for incineration efficiency and pollutant reduction, this paper introduces a model predictive control (MPC) strategy utilizing a back propagation neural network (BPNN). Traditional PID struggles with the nonlinearity and disturbances of process. Our approach involves construct...Show More

Furnace Temperature Control for MSWI Process Based on Neural Network Predictive Controller

Bokang Wang;Jian Tang;Heng Xia;Hao Tian;Tianzheng Wang;Zhiwei Wu

2024 36th Chinese Control and Decision Conference (CCDC)

Year: 2024 | Conference Paper |

Construction of flame image classification criteria and reference database for municipal solid waste incineration process

Xiaotong Pan;Jian Tang;Heng Xia;Hao Tian;Tianzheng Wang;Wen Xu

2023 35th Chinese Control and Decision Conference (CCDC)

Year: 2023 | Conference Paper |

Cited by: Papers (4)

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The flame combustion state inside the furnace is important feedback information for intelligent optimization control of the municipal solid waste incineration (MSWI) process. However, none of the existing studies on the identification of MSWI combustion state have proposed a combustion state classification criteria, which with actual physical significance and interpretability for the incineration ...Show More

Construction of flame image classification criteria and reference database for municipal solid waste incineration process

Xiaotong Pan;Jian Tang;Heng Xia;Hao Tian;Tianzheng Wang;Wen Xu

2023 35th Chinese Control and Decision Conference (CCDC)

Year: 2023 | Conference Paper |

Interpretable controlled object model of furnace temperature for MSWI process based on a novle linear regression decision tree

Heng Xia;Jian Tang;Tianzheng Wang;Hao Tian;Canlin Cui;Wen Xu

2023 35th Chinese Control and Decision Conference (CCDC)

Year: 2023 | Conference Paper |

Cited by: Papers (3)

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The furnace temperature is one of the most critical controlled variables in the municipal solid waste incineration (MSWI) process. The primary challenge of intelligent optimal control is to construct a high-precision and interpretable controlled object model in terms of furnace temperature. To address this problem, this article proposes a novel modeling method, i.e., linear regression decision tre...Show More

Interpretable controlled object model of furnace temperature for MSWI process based on a novle linear regression decision tree

Heng Xia;Jian Tang;Tianzheng Wang;Hao Tian;Canlin Cui;Wen Xu

2023 35th Chinese Control and Decision Conference (CCDC)

Year: 2023 | Conference Paper |

Furnace Temperature Control based on Adaptive TS-FNN for Municipal Solid Waste Incineration Process

Hao Tian;Jian Tang;Heng Xia;Tianzheng Wang;Canlin Cui;Xiaotong Pan

2023 35th Chinese Control and Decision Conference (CCDC)

Year: 2023 | Conference Paper |

Cited by: Papers (2)

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In the process of municipal solid waste incineration (MSWI), the stability of furnace temperature determines the running safety and pollution emission level. The furnace temperature is influenced by different uncertainty fluctuations and strong interference. This makes it difficult to effectively control using the PID algorithm. Aiming at the above problems, an adaptive TS fuzzy neural network (FN...Show More

Furnace Temperature Control based on Adaptive TS-FNN for Municipal Solid Waste Incineration Process

Hao Tian;Jian Tang;Heng Xia;Tianzheng Wang;Canlin Cui;Xiaotong Pan

2023 35th Chinese Control and Decision Conference (CCDC)

Year: 2023 | Conference Paper |

Combustion State Identification of Municipal Solid Waste Incineration Process Based on VGG19 Depth Feature Migration

Hao Tian;Jian Tang;Xiaotong Pan;Heng Xia;Tianzheng Wang;Zixuan Wang

2023 35th Chinese Control and Decision Conference (CCDC)

Year: 2023 | Conference Paper |

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The combustion stability of solid waste in the incinerator determines the operating efficiency and pollutant emission concentration of the municipal solid waste incineration (MSWI) process. At present, domain experts identity the combustion state and manually control the MSWI process has the problem of unstable identification results and low intelligence. A combustion state recognition method for ...Show More

Combustion State Identification of Municipal Solid Waste Incineration Process Based on VGG19 Depth Feature Migration

Hao Tian;Jian Tang;Xiaotong Pan;Heng Xia;Tianzheng Wang;Zixuan Wang

2023 35th Chinese Control and Decision Conference (CCDC)

Year: 2023 | Conference Paper |

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