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学者姓名：李晓理
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Abstract ：
The burning of fossil fuels is responsible for a large share of global electricity generation, leading to the emission of various atmospheric pollutants, such as sulfur dioxide (SO2 ). Due to the significant release of SO2 from coal combustion, wet flue gas desulfurization (WFGD) technologies are widely utilized in coal-powered plants. The design of WFGD modeling systems is essential for enhancing and managing the desulfurization process. However, WFGD processes in industrial settings are complex, featuring non-linear behavior, time delays, and dynamic uncertainties driven by environmental changes, making effective dynamic modeling a daunting task. This study presents an innovative FGD modeling system that combines machine learning, multi-model approaches, and dynamic neural model to address these challenges. The system achieves high accuracy in predicting SO2 emission concentration, even with fluctuating process dynamics. The proposed modeling system's effectiveness and practicality are validated through an examination of a real-world WFGD process. Moreover, its flexible structure, real-time capability, and exceptional performance highlight its broad applicability across many sectors.
Keyword ：
Nonlinear autoregressive-moving average-L2 Nonlinear autoregressive-moving average-L2 SO2 emission prediction SO2 emission prediction Machine learning Machine learning model model Wet flue gas desulphurisation Wet flue gas desulphurisation Adaptive learning Adaptive learning
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| GB/T 7714 | Liu, Quanbo , Li, Xiaoli , Wang, Kang . Real-time dynamic modelling of industrial WFGD process using an intelligence-based multi-model approach [J]. | MEASUREMENT , 2025 , 249 . |
| MLA | Liu, Quanbo 等. "Real-time dynamic modelling of industrial WFGD process using an intelligence-based multi-model approach" . | MEASUREMENT 249 (2025) . |
| APA | Liu, Quanbo , Li, Xiaoli , Wang, Kang . Real-time dynamic modelling of industrial WFGD process using an intelligence-based multi-model approach . | MEASUREMENT , 2025 , 249 . |
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Abstract ：
In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator faults. First, a novel augmented plant is constructed by fusing the system state and the reference trajectory, which aims to transform the optimal fault-tolerant tracking control design with actuator faults into the optimal regulation problem of the conventional nonlinear error system. Subsequently, in order to ensure the normal execution of the online learning algorithm, a stability criterion condition is created to obtain an initial admissible tracking policy. Then, the constructed model neural network (NN) is pre-trained to recognize the system dynamics and calculate trajectory control. The critic and action NNs are constructed to output the approximate cost function and approximate tracking control, respectively. The Hamilton-Jacobi-Bellman equation of the error system is solved online through the action-critic framework. In theoretical analysis, it is proved that all concerned signals are uniformly ultimately bounded according to the Lyapunov principle. The tracking control law can approach the optimal tracking control within a finite approximation error. Finally, two experimental examples are conducted to indicate the effectiveness and supe-riority of the developed fault-tolerant tracking control scheme.
Keyword ：
neural network (NN) neural network (NN) uni-form ultimate boundedness uni-form ultimate boundedness online fault-tolerant tracking design online fault-tolerant tracking design non-affine nonlinear systems non-affine nonlinear systems Adaptive critic control Adaptive critic control
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| GB/T 7714 | Wang, Ding , Hu, Lingzhi , Li, Xiaoli et al. Online Fault-Tolerant Tracking Control With Adaptive Critic for Nonaffine Nonlinear Systems [J]. | IEEE-CAA JOURNAL OF AUTOMATICA SINICA , 2025 , 12 (1) : 215-227 . |
| MLA | Wang, Ding et al. "Online Fault-Tolerant Tracking Control With Adaptive Critic for Nonaffine Nonlinear Systems" . | IEEE-CAA JOURNAL OF AUTOMATICA SINICA 12 . 1 (2025) : 215-227 . |
| APA | Wang, Ding , Hu, Lingzhi , Li, Xiaoli , Qiao, Junfei . Online Fault-Tolerant Tracking Control With Adaptive Critic for Nonaffine Nonlinear Systems . | IEEE-CAA JOURNAL OF AUTOMATICA SINICA , 2025 , 12 (1) , 215-227 . |
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Abstract ：
Efficient flotation beneficiation heavily relies on accurate flotation condition recognition based on monitored froth video. However, the recognition accuracy is hindered by limitations of extracting temporal features from froth videos and establishing correlations between complex multi-modal high-order data. To address the difficulties of inadequate temporal feature extraction, inaccurate online condition detection, and inefficient flotation process operation, this paper proposes a novel flotation condition recognition method named the multi-modal temporal hypergraph neural network (MTHGNN) to extract and fuse multi-modal temporal features. To extract abundant dynamic texture features from froth images, the MTHGNN employs an enhanced version of the local binary pattern algorithm from three orthogonal planes (LBP-TOP) and incorporates additional features from the three-dimensional space as supplements. Furthermore, a novel multi-view temporal feature aggregation network (MVResNet) is introduced to extract temporal aggregation features from the froth image sequence. By constructing a temporal multi-modal hypergraph neural network, we encode complex high-order temporal features, establish robust associations between data structures, and flexibly model the features of froth image sequence, thus enabling accurate flotation condition identification through the fusion of multi-modal temporal features. The experimental results validate the effectiveness of the proposed method for flotation condition recognition, providing a foundation for optimizing flotation operations.
Keyword ：
MVResNet MVResNet froth image sequence froth image sequence temporal HGNN temporal HGNN multi-modal fusion multi-modal fusion flotation condition identification flotation condition identification
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| GB/T 7714 | Fan, Zunguan , Feng, Yifan , Wang, Kang et al. Multi-Modal Temporal Hypergraph Neural Network for Flotation Condition Recognition [J]. | ENTROPY , 2024 , 26 (3) . |
| MLA | Fan, Zunguan et al. "Multi-Modal Temporal Hypergraph Neural Network for Flotation Condition Recognition" . | ENTROPY 26 . 3 (2024) . |
| APA | Fan, Zunguan , Feng, Yifan , Wang, Kang , Li, Xiaoli . Multi-Modal Temporal Hypergraph Neural Network for Flotation Condition Recognition . | ENTROPY , 2024 , 26 (3) . |
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Abstract ：
The process of smelting non-ferrous metals results in significant emissions of flue gas that contains sulfur dioxide (SO 2$$ {}_2 $$), which is very harmful to the environment. Through precise control of converter inlet temperature, it is feasible to enhance the conversion ratio of SO 2$$ {}_2 $$ and simultaneously mitigate environmental pollution by generating acid from flue gas. Because of the high degree of uncertainty in smelting process, converter inlet temperature is challenging to regulate and controller frequently needs updating. To improve control performance and decrease controller update times, an event-triggered neural network model predictive control (ETNMPC) strategy is proposed. First, long short-term memory (LSTM) prediction model and model predictive controller are developed. Second, it is decided whether to update the existing controller by designing an event-triggered mechanism. Finally, using real data from a copper facility in Jiangxi Province, the temperature control experiment of converter inlet is carried out. Simulation results demonstrate that the proposed ETNMPC outperforms conventional time-triggered method in terms of control performance, greatly lowers the times of controller updates, and significantly lowers computation costs and communication burden. Key findings: (1) LSTM neural network is used to establish the predictive model of converter inlet temperature and model predictive controller is designed. (2) Two different event-triggered mechanisms with fixed threshold are designed. (3) Event-triggered neural network predictive control can effectively reduce the number of controller triggers, save computing resources, and improve system performance. image
Keyword ：
neural network predictive control neural network predictive control event-triggered mechanism event-triggered mechanism tracking control tracking control flue gas acid production flue gas acid production
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| GB/T 7714 | Liu, Minghua , Li, Xiaoli , Wang, Kang . Neural network predictive control of converter inlet temperature based on event-triggered mechanism in flue gas acid production [J]. | OPTIMAL CONTROL APPLICATIONS & METHODS , 2024 , 45 (4) : 1815-1831 . |
| MLA | Liu, Minghua et al. "Neural network predictive control of converter inlet temperature based on event-triggered mechanism in flue gas acid production" . | OPTIMAL CONTROL APPLICATIONS & METHODS 45 . 4 (2024) : 1815-1831 . |
| APA | Liu, Minghua , Li, Xiaoli , Wang, Kang . Neural network predictive control of converter inlet temperature based on event-triggered mechanism in flue gas acid production . | OPTIMAL CONTROL APPLICATIONS & METHODS , 2024 , 45 (4) , 1815-1831 . |
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Abstract ：
In this article, a global output feedback control scheme is developed for a class of uncertain nonlinear systems subject to input quantization and unknown output function. By employing a time-varying gain and a time-invariant gain, we address the challenges posed by quantization errors and nonlinear functions with an unknown linear growth rate. Additionally, we determine an allowable measurement sensitivity error by solving a straightforward inequality. We demonstrate that the proposed scheme ensures global asymptotic stability for the system and guarantees that all signals of the closed-loop system remain bounded. Finally, we validate the proposed approach through a mathematical example and an experiment conducted on the QUBE-Servo 2 equipped with an inertial disc module.
Keyword ：
Global asymptotic stability Global asymptotic stability unknown output function unknown output function Quantization (signal) Quantization (signal) Nonlinear systems Nonlinear systems Information science Information science quantization quantization Sensitivity Sensitivity networked control systems (NCSs) networked control systems (NCSs) Hysteresis Hysteresis Lyapunov methods Lyapunov methods Output feedback Output feedback Measurement uncertainty Measurement uncertainty Symmetric matrices Symmetric matrices Asymptotic stability Asymptotic stability
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| GB/T 7714 | Yu, Xiaowei , Li, Xiaoli . Global Asymptotic Stabilization Control for Uncertain Nonlinear Systems With Input Quantization and Unknown Output Function [J]. | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS , 2024 , 54 (12) : 7528-7533 . |
| MLA | Yu, Xiaowei et al. "Global Asymptotic Stabilization Control for Uncertain Nonlinear Systems With Input Quantization and Unknown Output Function" . | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 54 . 12 (2024) : 7528-7533 . |
| APA | Yu, Xiaowei , Li, Xiaoli . Global Asymptotic Stabilization Control for Uncertain Nonlinear Systems With Input Quantization and Unknown Output Function . | IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS , 2024 , 54 (12) , 7528-7533 . |
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Abstract ：
It is well established that the configuration and operation of variable speed air source heat pumps (VS ASHPs) can significantly influence their frosting performance. However, there is currently no effective method to conveniently and accurately evaluate the frosting suppression performance of these units. This paper addresses this gap by proposing a novel evaluation method based on a frosting suppression map for VS ASHPs. Firstly, an experimental setup with four ASHP units and developed frosting suppression maps is described. Second, a method for evaluating the frosting suppression performance of VS ASHP is developed based on the map. Thirdly, a comprehensive evaluation of the frosting suppression performance of the experimental unit is carried out. It is shown that the beta values of the four units under the constitutive configuration were 0.74, 0.12, 0.21, and 0.52, and the frosting suppression performance was evaluated as Good, Poor, Fair, and Average, respectively. It could be enhanced and improved to 0.89 (Excellent), 0.24 (Fair), 0.64 (Good), and 0.63 (Good) after applying the frosting suppression operation method. The proposed novel frosting suppression evaluation method is simple and easy to implement, which could contribute to further guiding manufacturers to improve the frosting suppression performance of VS ASHPs.
Keyword ：
Evaluation method Evaluation method Variable speed Variable speed performance performance Frosting suppression performance map Frosting suppression performance map Evaluating the frosting suppression Evaluating the frosting suppression Air source heat pump Air source heat pump
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| GB/T 7714 | Lin, Yao , Luo, Jianfei , Luo, Qing et al. Evaluation method and enhanced strategy for frosting suppression performance of variable speed air source heat pump based on frosting suppression performance map [J]. | ENERGY AND BUILDINGS , 2024 , 325 . |
| MLA | Lin, Yao et al. "Evaluation method and enhanced strategy for frosting suppression performance of variable speed air source heat pump based on frosting suppression performance map" . | ENERGY AND BUILDINGS 325 (2024) . |
| APA | Lin, Yao , Luo, Jianfei , Luo, Qing , Li, Xiaoli , Wang, Wei , Sun, Yuying . Evaluation method and enhanced strategy for frosting suppression performance of variable speed air source heat pump based on frosting suppression performance map . | ENERGY AND BUILDINGS , 2024 , 325 . |
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Abstract ：
This paper investigates the issue of adaptive finite-time tracking for nonlinear systems with both quantized input and states. More specially, a saturated quantized input is applied for the input quantization. By constructing a novel high-gain fuzzy state observer, the issues of unknown nonlinearities and discontinuous quantized signals are addressed. Then an adaptive backstepping controller involving the fuzzy logic systems is developed. It is verified that, with the designed control method, all signals of the closed-loop system are bounded, and the tracking error can be made small by choosing the design parameters suitably. Finally, a simulation example is studied to show the effectiveness of the control scheme.
Keyword ：
High-gain Observer High-gain Observer Fuzzy Logic Systems Fuzzy Logic Systems Quantized States Quantized States Finite-time Tracking Finite-time Tracking
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| GB/T 7714 | Yu, Xiaowwi , Li, Xiaoli . Fuzzy Finite-Time Tracking Control of Nonlinear Systems with Quantized States and Saturated Quantized Input [J]. | 2024 43RD CHINESE CONTROL CONFERENCE, CCC 2024 , 2024 : 745-752 . |
| MLA | Yu, Xiaowwi et al. "Fuzzy Finite-Time Tracking Control of Nonlinear Systems with Quantized States and Saturated Quantized Input" . | 2024 43RD CHINESE CONTROL CONFERENCE, CCC 2024 (2024) : 745-752 . |
| APA | Yu, Xiaowwi , Li, Xiaoli . Fuzzy Finite-Time Tracking Control of Nonlinear Systems with Quantized States and Saturated Quantized Input . | 2024 43RD CHINESE CONTROL CONFERENCE, CCC 2024 , 2024 , 745-752 . |
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Abstract ：
In this study, a finite-time adaptive prescribed performance control scheme is investigated for multi-input multi-output systems with input friction and backlash. The novel fixed-time neuro disturbance observer (Fix-TNDO) and fixed-time command filter (Fix-TCF) are constructed to ensure fast response of the controlled systems with settling time being determined regardless of initial states. The uncertainties caused by unknown smooth functions are handled by neural network approximators, then input friction and system disturbances are accurately compensated by Fix-TNDO. Meanwhile, the employed Fix-TCF is utilized to avoid repeated differentiation of virtual control signals during controller design. In particular, prescribed convergence of tracking errors for multi-input multi-output nonlinear system is ensured by finite-time performance function. Finally, simulation and experiment results demonstrate the feasibility and effectiveness of the proposed control strategy.
Keyword ：
Fixed-time command filter Fixed-time command filter Finite-time prescribed performance control Finite-time prescribed performance control Input friction and backlash Input friction and backlash MIMO nonlinear system MIMO nonlinear system Fixed-time neuro-disturbance observer Fixed-time neuro-disturbance observer
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| GB/T 7714 | Li, Xiaoli , Zhang, Guoju , Sun, Guofa . Neuro-disturbance observer based finite-time adaptive control for MIMO system under input nonlinearity [J]. | NONLINEAR DYNAMICS , 2024 . |
| MLA | Li, Xiaoli et al. "Neuro-disturbance observer based finite-time adaptive control for MIMO system under input nonlinearity" . | NONLINEAR DYNAMICS (2024) . |
| APA | Li, Xiaoli , Zhang, Guoju , Sun, Guofa . Neuro-disturbance observer based finite-time adaptive control for MIMO system under input nonlinearity . | NONLINEAR DYNAMICS , 2024 . |
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Abstract ：
This article investigates the predefined-time tracking problem for high-order strict feedback system. 'Modified command filter can riot only avoid the "computational complexity explosion" phenomenon in traditional backstepping methods, but also alleviate the chattering problem caused by signum in conventional filters. A novel predefined-time compensation system is proposed to compensate for the decrease in control accuracy caused by filtering errors. Predefined-time command filtering controller is proposed by combining the backstepping mechanism and predefined-time theory, ensuring that the controlled system converges within a user-defined time. Finally, mathematical simulation demionstrates the rationality and effectiveness of the proposed control scheme.
Keyword ：
Modified command filter Modified command filter Error compensation mechanism Error compensation mechanism Predefined-time stability Predefined-time stability
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| GB/T 7714 | Zhang, Guoju , Li, Xiaoli . Predefined-Time Command Filtering Control for High-Order Strict Feedback System [J]. | 2024 43RD CHINESE CONTROL CONFERENCE, CCC 2024 , 2024 : 43-48 . |
| MLA | Zhang, Guoju et al. "Predefined-Time Command Filtering Control for High-Order Strict Feedback System" . | 2024 43RD CHINESE CONTROL CONFERENCE, CCC 2024 (2024) : 43-48 . |
| APA | Zhang, Guoju , Li, Xiaoli . Predefined-Time Command Filtering Control for High-Order Strict Feedback System . | 2024 43RD CHINESE CONTROL CONFERENCE, CCC 2024 , 2024 , 43-48 . |
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Abstract ：
Evolutionary algorithms have proven to be extremely effective at tackling multi-objective opti-mization problems (MOPs). However, when dealing with many-objective optimization problems (MaOPs), their performance frequently degrades, especially when the Pareto marking irregular shapes. The population pressure to choose the Pareto optimal front and address the generaliz-ability of different Pareto front shapes becomes more challenging as the number of objectives increases. We present a strength Pareto evolutionary algorithm based on adaptive reference points (SPEA/ARP) to address this problem. First, the reference points are updated using current and historical population information. The angles between the current demographic information and the predefined uniform reference points are used to select the active reference points, and the adaptive reference points are selected from the historical population information projected onto the reference plane. Second, the fitness function values are applied to classify the environmental selection criteria into two categories: 1) The angle distance scaling function using adaptive reference points is utilized to increase selection pressure, and the diversity of non-dominated solutions is balanced using the angle-based secondary selection technique. 2) Otherwise, the fitness function values are employed to choose the next generation of non-dominated solutions. Third, an aggregate fitness r-value generated by the angle distance scaling function is employed to construct matching pools that produce valid offsprings. Finally, extensive experiments are carried out to demonstrate SPEA/ARP performance by comparing it with six state-of-the-art many -objective evolutionary algorithms on 5-, 10-, 15-objective of 31 benchmark MaOPs. The experi-ments show that SPEA/ARP outperforms the compared algorithms.
Keyword ：
Irregular fronts Irregular fronts Strength Pareto evolutionary algorithm Strength Pareto evolutionary algorithm Matching pool Matching pool Angle distance scaling function Angle distance scaling function Adaptive reference points Adaptive reference points
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| GB/T 7714 | Li, Xin , Li, Xiaoli , Wang, Kang et al. A strength pareto evolutionary algorithm based on adaptive reference points for solving irregular fronts [J]. | INFORMATION SCIENCES , 2023 , 626 : 658-693 . |
| MLA | Li, Xin et al. "A strength pareto evolutionary algorithm based on adaptive reference points for solving irregular fronts" . | INFORMATION SCIENCES 626 (2023) : 658-693 . |
| APA | Li, Xin , Li, Xiaoli , Wang, Kang , Yang, Shengxiang . A strength pareto evolutionary algorithm based on adaptive reference points for solving irregular fronts . | INFORMATION SCIENCES , 2023 , 626 , 658-693 . |
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