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Learning-Based Predictive control of Switched Nonlinear Systems via Koopman Modeling Approach

Journal of Systems Science & Complexity 2025年第2期38卷 691-716页

作者： NING Zepeng FANG Xu LI Yibei XIE Lihua School of Electrical and Electronic Engineering Nanyang Technological University Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences

This paper proposes a data-driven learning-based approach to predictive control for switched nonlinear systems subject to state and control constraints and external stochastic disturbances. A switched Koopman modeling framework is developed, where a multi-mode neural network for state lifting is trained simultaneously with Koopman operators and state reconstruction matrices for all *** framework facilitates the construction of the switched linear Koopman model in a transformed space and effectively captures the dynamics of the original nonlinear system. A switched predictive control strategy is then designed to regulate the switched Koopman model with constrained states and control inputs against both the stochastic disturbances and the uncertainties introduced by the lifting neural network. The proposed control scheme ensures mean-square stability and guarantees boundedness during the online phase. Furthermore, boundedness analysis is performed to determine the bounded set of the original system state across all admissible switching sequences. The effectiveness of the proposed methodology is demonstrated through a case study of a gene regulatory network.

关键词： Data-driven machine learning model predictive control stochastic systems switched Koopman model switched nonlinear systems

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Microstructure and mechanical properties stability of pre-hardening treatment in Al-Cu alloys for pre-hardening forming process

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International Journal of Minerals,Metallurgy and Materials 2024年第3期31卷 539-551页

作者： Liping Tang Pengfei Wei Zhili Hu Qiu Pang Hubei Longzhong laboratory Xiangyang 441000China Hubei Key Laboratory of Advanced Technology for Automotive Components School of Automotive EngineeringWuhan University of TechnologyWuhan 430070China Hubei Engineering Research Center for Green&Precision Material Forming Wuhan University of TechnologyWuhan 430070China Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education School of Machinery and AutomationWuhan University of Science and TechnologyWuhan 430081China

The stability of the microstructure and mechanical properties of the pre-hardened sheets during the pre-hardening forming(PHF)process directly determines the quality of the formed *** microstructure stability of the pre-hardened sheets was in-vestigated by differential scanning calorimetry(DSC),transmission electron microscopy(TEM),and small angle X-ray scattering(SAXS),while the mechanical properties and formability were analyzed through uniaxial tensile tests and formability *** results in-dicate that the mechanical properties of the pre-hardened alloys exhibited negligible changes after experiencing 1-month natural aging(NA).The deviations of ultimate tensile strength(UTS),yield strength(YS),and sheet formability(Erichsen value)are all less than 2%.Also,after different NA time(from 48 h to 1 month)is applied to alloys before pre-hardening treatment,the pre-hardened alloys possess stable microstructure and mechanical properties as ***,with the extension of NA time before pre-hardening treatment from 48 h to 1 month,the contribution of NA to the pre-hardening treatment is *** a yield strength increment of 20 MPa is achieved,with no loss in *** limited enhancement is mainly attributed to the fact that only a limited number of clusters are transformed into Guinier-Preston(GP)zones at the early stage of pre-hardening treatment,and the formation ofθ''phase inhibits the nucleation and growth of GP zones as the precipitated phase evolves.

关键词： Al-Cu alloy pre-hardened alloy natural aging mechanical properties microstructure

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Model reference adaptive control of unknown control gain and asymmetrical static output constraints 41

Model reference adaptive control of unknown control gain and...

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第41届中国控制会议

作者： Penghao Chen Fei Liu Key Laboratory of Advanced Process Control for Light Industry Ministry of EducationInstitute of AutomationJiangnan University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The model reference adaptive control(MRAC) issue is addressed for a class of first-order linear time-invariant system(LTIS) with unknown control gain and asymmetric static output *** output constraints is efficiently handled by incorporating a barrier Lyapunov function(BLF).Completely unknown control gain is handled based on the Nussbaum *** the aid of Lyapunov synthesis method,the adaptive laws of unknown parameters are *** the properties of BLF and Barbalat's Lemma,it is proved that the tracking error converges asymptotically to zero while the output satisfies the *** comparison of the two simulation results is employed to demonstrate the efficacy of the suggested MRAC algorithm.

关键词： Model reference adaptive control Asymmetrical static output constraints Barrier Lyapunov function Unknown control gain Nussbaum function

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A Novel GNN-Based Node Importance Ranking Method in a Heterogeneous Network 7th

A Novel GNN-Based Node Importance Ranking Method in a Hete...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Li, Shuyu Ji, Dedong Wang, Jingwei Xia, Weiguo Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China Shenyang Aircraft Design and Research Institute Shenyang China

ISBN: (纸本)9789819733231

In a heterogeneous network, a reliable importance ranking of nodes can provide a useful reference for decision-making. Nevertheless, existing node importance ranking methods may not effectively integrate the characteristics of the edges and nodes in the graph, as well as the structural information. In this paper, a novel graph neural network-based heterogeneous network node importance ranking (GNN-HNNIR) method is proposed to rank the importance of different functional nodes in a heterogeneous network. GNN-HNNIR can adjust the node importance score based on those of neighboring nodes, which employ a multi-head attention mechanism to aggregate scores by pooling information from edges, nodes, and the graph structure. Finally, numerical experiments show that GNN-HNNIR can effectively evaluate the importance scores of different nodes with given small amount of data for training. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Heterogeneous networks

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Efficiency analysis of sorption-enhanced method in steam methane reforming process

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Carbon Resources Conversion 2023年第2期6卷 132-141页

作者： Yaowei Hu Lu Liu Kai Xu Yuncai Song Jieying Jing Huiyan Zhang Jie Feng State Key Laboratory of Clean and Efficient Coal Utilization Taiyuan University of TechnologyTaiyuan 030024ShanxiChina Key Laboratory of Energy Thermal Conversion and Process Measurement and Control of Ministry of Education Southeast UniversityNanjing 210096China

The sorption-enhanced method can change the thermodynamic equilibrium by absorbing CO_(2).However,it also brings about the problems of high regeneration temperature of adsorbent and large regeneration energy *** order to study the impact of enhanced adsorption methods on the overall energy cost of the system in the hydrogen production process,this paper analyzes and compares steam methane reforming and reactive adsorption-enhanced steam methane reforming with the energy consumption of hydrogen production products as the evaluation *** results showed that the energy consumption per unit hydrogen production decreased from 276.21 MJ/kmol to 131.51 MJ/kmol,and the decomposition rate of H2O increased by more than 20%after the addition of adsorption enhancement *** is proved that the advantage of sorption enhanced method on pre-separation of CO_(2)in the product makes up for the disadvantage of energy consumption of adsorbent *** addition,the ability of the process to obtain H element is improved by the high decomposition rate of H2O,which realizes a more rational distribution of the element.

关键词： Sorption-enhanced method Steam methane reforming Reactive sorption enhanced steam methane reforming Pressure swing adsorption process simulation

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Prediction Method of Mixed Gas Consumption in Hot Rolling Based on Improved K-Medoids Working Condition Division

Prediction Method of Mixed Gas Consumption in Hot Rolling Ba...

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2023 China Automation Congress, CAC 2023

作者： Li, Hao Xu, Demin Zhou, Fan Zhao, Jun Ministry of Education Key Laboratory of Intelligent Control and Optimization for Industrial Equipment China School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798350303759

The prediction of mixed gas consumption in hot rolling production is of great significance in gas production-consumption balance and energy saving. However, in the actual production process of hot rolling, the complexity of production environment and the strong coupling of production processes lead to the complexity of working conditions, which brings great challenges to the prediction of mixed gas consumption. A prediction method of hot rolling mixed gas consumption based on improved K-Medoids working condition division is proposed in this paper. Based on Chebyshev's theorem, the method uses more robust median and median absolute deviation to evaluate the outliers in the cluster at each iteration in terms of distance, and further verifies from the perspective of density to complete the division of normal working conditions and abnormal working conditions. On this basis, considering the time dependence of hot rolling data, the prediction model of mixed gas consumption under corresponding working conditions was established by using the Long Short-Term Memory (LSTM) neural network. In order to verify the effectiveness of the proposed method, the actual industrial field data are used. The simulation results show that the proposed method has high prediction accuracy and is suitable for the prediction of mixed gas consumption in hot rolling. © 2023 IEEE.

关键词： Forecasting

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Learning Adaptive Mapless Navigation Skills Through Evidential Deep Learning

Learning Adaptive Mapless Navigation Skills Through Evidenti...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Zhao, Cancan Yan, Yufeng Liu, Xuhao Zhang, Shuai Ouyang, Bo Hefei University of Technology School of Management Hefei China Hefei University of Technology The Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei China

ISBN: (纸本)9798350327182

Traditional navigation methods tend to design and train navigation skills based on the consideration of multi-scenario applicability and perform well in general scenarios. However, this results in sub-optimal navigation performance in some context-specific scenarios, such as navigating through open or crowded scenarios. While some existing navigation skills can achieve satisfactory performance in context-specific scenarios, e.g., using PID in open scenarios and reinforcement learning-based training methods in crowded scenarios. Most methods currently do without consideration of the integration of navigation skills and contextual understanding. To address this gap, we propose an adaptive mapless navigation method to utilize the optimal capabilities of each skill corresponding to the context-specific scenario. Specifically, we package several existing navigation skills and train a scenario classifier to enable the agent to automatically select the most appropriate skill based on the current scenario. Furthermore, we incorporate evidential deep learning (EDL) to assess classification uncertainty and ensure the safe switching of navigation skills. Our method was tested in both simulated and real scenarios, and the results of the experiments confirmed the effectiveness and generalization of our method. Moreover, the proposed method exhibits notably enhanced, context-sensitive efficiency within a hybrid multi-scenario setting, in comparison to a single navigation skill. © 2023 IEEE.

关键词： Navigation

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Preparation of biomass-derived carbon loaded with MnO_(2) as lithium-ion battery anode for improving its reversible capacity and cycling performance

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Frontiers of Chemical Science and Engineering 2024年第1期18卷 107-120页

作者： Likai Zhu Huaping Lin Wenli Zhang Qinhui Wang Yefeng Zhou National&Local United Engineering Research Centre for Chemical Process Simulation and Intensification Chemical Process Simulation and Optimization Engineering Research Center of Ministry of EducationXiangtan UniversityXiangtan 411100China Guangdong Provincial Key Laboratory of Plant Resources Biorefinery School of Chemical Engineering and Light IndustryGuangdong University of TechnologyGuangzhou 510006China State Key Laboratory of Clean Energy Utilization Zhejiang UniversityHangzhou 310027China

Biomass-derived carbon materials for lithiumion batteries emerge as one of the most promising anodes from sustainable ***,improving the reversible capacity and cycling performance remains a long-standing *** combining the benefits of K2CO_(3) activation and KMnO_(4) hydrothermal treatment,this work proposes a two-step activation method to load MnO_(2) charge transfer onto biomass-derived carbon(KAC@MnO_(2)).Comprehensive analysis reveals that KAC@MnO_(2) has a micro-mesoporous coexistence structure and uniform surface distribution of MnO_(2),thus providing an improved electrochemical ***,KAC@MnO_(2) exhibits an initial chargedischarge capacity of 847.3/1813.2 mAh·g^(-1) at 0.2 A·g^(-1),which is significantly higher than that of direct pyrolysis carbon and K2CO_(3) activated carbon,***,the KAC@MnO_(2) maintains a reversible capacity of 652.6 mAh·g^(-1) after 100 *** at a high current density of 1.0 A·g^(-1),KAC@MnO_(2) still exhibits excellent long-term cycling stability and maintains a stable reversible capacity of 306.7 mAh·g^(-1) after 500 *** with reported biochar anode materials,the KAC@MnO_(2) prepared in this work shows superior reversible capacity and cycling ***,the Li+insertion and de-insertion mechanisms are verified by ex situ X-ray diffraction analysis during the chargedischarge process,helping us better understand the energy storage mechanism of KAC@MnO_(2).

关键词： biomass-derived carbon MnO_(2) lithium-ion batteries anode material high reversible capacity

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Feedback Generative Adversarial Network With Channel-Space Attention for Image-Based Optimal Path Search Planning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4293-4307页

作者： Sun, Tao Li, Jian-Sheng Zhang, Yi-Fan Ru, Xin-Feng Wang, Ke Tsinghua University Department of Automation Beijing100084 China Dalian University of Technology School of Control Science and Engineering Dalian116024 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Tongji University School of Economics and Management Shanghai200092 China

Path planning and seeking is one of the most challenging and interesting problems in the field of artificial intelligence. In this article, we propose a new image-based path planning algorithm to overcome traditional design concepts based on complex topological networks. Specifically, a novel feedback generative adversarial network learning model with channel-space attention (CSA-FGAN) is developed to search and plan an optimal path. It is worth noting that the input and output of the proposed feedback learning model are RGB images with complex spatial obstacle environment maps and RGB images with feasible paths, respectively. In particular, in order to further enhance the feature extraction ability and path prediction accuracy of image data, the feedback attention mechanism controls and improves the depth of the network by forming a closed loop of the proposed learning model. Final, three application scenario image examples are conducted to verify the superiority of the proposed path planning policy. © 2020 IEEE.

关键词： Motion planning

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Unveiling the geometric site dependent activity of spinel Co_(3)O_(4)for electrocatalytic chlorine evolution reaction

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Journal of Energy Chemistry 2024年第5期92卷 95-103页

作者： Linke Cai Yao Liu Jingfang Zhang Qiqi Jia Jiacheng Guan Hongwei Sun Yu Yu Yi Huang Key Laboratory of Pesticide&Chemical Biology of Ministry of Education Engineering Research Center of Photoenergy Utilization for Pollution Control and Carbon Reduction of Ministry of EducationCollege of ChemistryCentral China Normal UniversityWuhan 430079HubeiChina Key Laboratory of Green Chemical Engineering Process of Ministry of Education Engineering Research Center of Phosphorus Resources Development and Utilization of Ministry of EducationHubei Key Laboratory of Novel Reactor and Green Chemical TechnologySchool of Chemical Engineering&PharmacyWuhan Institute of TechnologyWuhan 430205HubeiChina College of Materials Science and Engineering Fuzhou UniversityFuzhou 350108FujianChina School of Chemistry and Chemical Engineering Anhui UniversityHefei 230601AnhuiChina

Spinel cobalt oxide(Co_(3)O_(4)),consisting of tetrahedral Co^(2+)(CoTd)and octahedral Co^(3+)(CoOh),is considered as promising earth-abundant electrocatalyst for chlorine evolution reaction(CER).Identifying the catalytic contribution of geometric Co site in the electrocatalytic CER plays a pivotal role to precisely modulate electronic configuration of active Co sites to boost ***,combining density functional theory calculations and experiment results assisted with operando analysis,we found that the Co_(Oh) site acts as the main active site for CER in spinel Co_(3)O_(4),which shows better Cl^(-)adsorption and more moderate intermediate adsorption toward CER than CoTd site,and does not undergo redox transition under CER condition at applied *** by above findings,the oxygen vacancies were further introduced into the Co_(3)O_(4) to precisely manipulate the electronic configuration of Co_(Oh) to boost Cl^(-)adsorption and optimize the reaction path of CER and thus to enhance the intrinsic CER activity *** work figures out the importance of geometric configuration dependent CER activity,shedding light on the rational design of advanced electrocatalysts from geometric configuration optimization at the atomic level.

关键词： Chlorine evolution reaction Geometry effects Active chlorine Electronic configuration optimization Spinel oxides

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