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第43届中国控制会议

作者： MAO Yawen XU Chen School of science Jiangnan University Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) School of Internet of Things EngineeringJiangnan University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Outliers usually occur during data collection process and can lead to poor system identification performance. This paper considers the parameter estimation algorithms for Hammerstein systems whose output measurements are contaminated with additive outliers. By incorporating a lasso-type penalty on the outlier vector, a regularization based least squares identification algorithm that can interactively estimate the system parameters and outliers is proposed based on the auxiliary model identification idea. To further reduce the impact of outliers on the identification effect, each observation is assigned an individual weight, which decreases as the number of iterations increases once the corresponding data is determined to be an outlier. Finally,the outliers can be excluded from the contaminated data without any prior knowledge and the estimation bias is reduced. A numerical example is given to confirm the effectiveness of the proposed algorithm.

关键词： System identification Hammerstein system Outlier Regularization Auxiliary model

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Scaled Bipartite Consensus controller Design for Second-Order Multi-Agent Systems with Mixed Time-Delays

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Journal of Systems Science & Complexity 2022年第3期35卷 888-908页

作者： YANG Ruitian PENG Li YANG Yongqing ZHAO Huarong Research Center of Engineering Applications for IOT Jiangnan UniversityWuxi 214122China Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) School of ScienceJiangnan UniversityWuxi 214122China

The scaled bipartite consensus of second-order multi-agent systems is investigated in this *** internal delay and distributed delay are also considered in the dynamic model of each agent,in which the delays can be time-varying and *** communication topology among agents is assumed to be directed and structurally *** one hand,in order to guarantee scaled bipartite consensus of second-order multi-agent systems,an adaptive periodically intermittent control protocol is *** the other hand,some consensus criteria in the form of matrix inequalities are obtained by using Jensen inequality,Lyapunov stability theory and graph ***,a numerical simulation example is given to demonstrate the feasibility of theoretical results.

关键词： Adaptive control mixed delays multi-agent systems periodically intermittent control scaled bipartite consensus

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Dynamic Iterative Learning control for Relative Trajectory Tracking with Nonrepetitive Leader Path 13

Dynamic Iterative Learning Control for Relative Trajectory T...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Wang, Yiming Wang, Guina Tao, Hongfeng Chen, Yiyang School of Mechanical and Electrical Engineering Soochow University Suzhou215137 China Jiangnan University Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Wuxi214122 China

ISBN: (纸本)9798350361674

This paper proposes a collaborative iterative learning control scheme with optimal leader path planning strategy. Due to the demonds on repetitive tasks and static references under traditional ILC framework, it cannot fit the complex circumstances with multiple collaborative systems or satisfy certain control request on specific application. This paper introduces a dynamic norm-optimal iterative learning control (NOILC) framework based on an improved coordinate descent algorithm. Under the aforementioned framework, an optimal leader path can be found to fit certain performance requirements, i.e. energy reduction. Finally, the simulation results on a combined complex system verify the effectiveness of the proposed algorithm. © 2024 IEEE.

关键词： Convex optimization

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The Impact of Emotional Intelligence, Managerial Intelligence, and Transformational Leadership on Multidimensional Public Project Success

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IEEE engineering Management Review 2022年第4期50卷 111-126页

作者： Fareed, Muhammad Zeeshan Su, Qin Naqvi, Najam Abbas Xian Jiaotong University School of Management Xian710049 China State Key Laboratory for Manufacturing Systems Engineering Xi'an710049 China Key Laboratory of the Ministry of Education for Process Control and Efficiency Engineering Xi'an710049 China Institute of Space Technology National Center of GIS and Space Applications Islamabad44000 Pakistan

The project manager's role and influence on the project's overall outcome have fascinated many academicians, researchers, and practitioners. The project manager's leadership and human skills play a vital role in the project's outcome;therefore, it is imperative for these competencies to be identified, learned, and leadership styles to be adopted. This study aims to define the most relevant competencies to multidimensional project success and their interrelationship. The quantitative method was used by applying a survey to project managers and team members working in the public sector of Pakistan. The results suggest that a combination of emotional, managerial intelligence, and transformational leadership are stronger predictors of multidimensional public project success. This study has shown that management and leadership need to be integrated to achieve better results. Project managers need to combine soft and hard skills, leadership competencies, and management to engage with people and be effective in terms of processes, tasks, and objectives. © 1973-2011 IEEE.

关键词： Project management

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Fuzzy-Model-Based Finite Frequency Fault Detection Filtering Design for Two-Dimensional Nonlinear Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第10期11卷 2099-2110页

作者： Meng Wang Huaicheng Yan Jianbin Qiu Wenqiang Ji Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationSchool of Information Science and EngineeringEast China University of Science and TechnologyShanghai 200237China Research Institute of Intelligent Control and Systems School of AstronauticsHarbin Institute of TechnologyHarbin 150080China School of Artificial Intelligence Hebei University of TechnologyTianjin 300401China IEEE

This article studies the fault detection filtering design problem for Roesser type two-dimensional(2-D)nonlinear systems described by uncertain 2-D Takagi-Sugeno(T-S)fuzzy ***,fuzzy Lyapunov functions are constructed and the 2-D Fourier transform is exploited,based on which a finite frequency fault detection filtering design method is proposed such that a residual signal is generated with robustness to external disturbances and sensitivity to *** has been shown that the utilization of available frequency spectrum information of faults and disturbances makes the proposed filtering design method more general and less conservative compared with a conventional nonfrequency based filtering design ***,with the proposed evaluation function and its threshold,a novel mixed finite frequency H_(∞)/H_(-)fault detection algorithm is developed,based on which the fault can be immediately detected once the evaluation function exceeds the ***,it is verified with simulation studies that the proposed method is effective and less conservative than conventional non-frequency and/or common Lyapunov function based filtering design methods.

关键词： Fault diagnosis finite frequency specifications mixed H_(∞)/H_(-)performance two-dimensional nonlinear systems

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Regularization based reweighted estimation algorithm for nonlinear systems in presence of outliers 43

Regularization based reweighted estimation algorithm for non...

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43rd Chinese control Conference, CCC 2024

作者： Yawen, Mao Chen, Xu Jiangnan University School of science Wuxi214122 China Jiangnan University Key Laboratory of Advanced Process Control for Light Industry Ministry of Education School of Internet of Things Engineering Wuxi214122 China

ISBN: (纸本)9789887581581

Outliers usually occur during data collection process and can lead to poor system identification performance. This paper considers the parameter estimation algorithms for Hammerstein systems whose output measurements are contaminated with additive outliers. By incorporating a lasso-type penalty on the outlier vector, a regularization based least squares identification algorithm that can interactively estimate the system parameters and outliers is proposed based on the auxiliary model identification idea. To further reduce the impact of outliers on the identification effect, each observation is assigned an individual weight, which decreases as the number of iterations increases once the corresponding data is determined to be an outlier. Finally, the outliers can be excluded from the contaminated data without any prior knowledge and the estimation bias is reduced. A numerical example is given to confirm the effectiveness of the proposed algorithm. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Statistics

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Dynamic Prediction on Driving Attitude of Tunnel Boring Machine (TBM): An Automated Deep Learning Approach 18th

Dynamic Prediction on Driving Attitude of Tunnel Boring Mach...

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18th Conference of the Associated Research Centers for the Urban Underground Space, ACUUS 2023

作者： Wang, Ziyi Pan, Yue Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure Department of Civil Engineering Shanghai Jiao Tong University Shanghai200240 China Engineering Research Center of Building Energy Efficiency Control and Evaluation Ministry of Education Anhui China

ISBN: (纸本)9789819712564

This paper proposes an automated deep learning (AutoDL) framework for the dynamic driving attitude prediction of the tunnel boring machine (TBM) in tunnel construction. A standard process is proposed for the automated deep learning framework, including data preprocessing, optimal hyperparameter tuning, algorithm selection, and model performance evaluation, which can intelligently learn the time-varying monitoring data collected by the smart sensors installed on TBM. Moreover, a prediction interval is carefully designed to well consider the uncertainty, which is stable enough to raise the reliability of the prediction results. To validate the effectiveness and practicability of the proposed approach, it is applied in a TBM project for a natural gas pipeline network in Chongming Island–Changxing Island–Pudong New Area in Shanghai. Results indicate that the proposed automated deep learning with p swarm optimization (PSO) algorithm greatly reduces the requirements of model training evaluation on the professional knowledge of developers, which can return not only high-accuracy predictions, but also interval-based predictions considering uncertainties. As for the engineering practice value, the deviation of TBM driving attitude in each segment ring can be dynamically and reliably estimated, which provides valuable evidence for managers to timely adjust the TBM operation to ensure the project quality. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Natural gas pipelines

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Efficient production of 14α‑OH‑AD by engineered Mycolicibacterium neoaurum via coupled cofactor and reconstructed electron transport system

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Systems Microbiology and Biomanufacturing 2023年第2期3卷 358-369页

作者： Chenwei Zhang Yanbing Shen Yuanyuan Gao Zehui Zan Min Wang Key Laboratory of Industrial Fermentation Microbiology Ministry of EducationTianjin Key Laboratory of Industrial MicrobiologyTianjin University of Science and TechnologyTianjinChina Engineering Research Center of Microbial Metabolism and Fermentation Process Control College of BiotechnologyTianjin University of Science and TechnologyTianjin 300457People’s Republic of China

14α-hydroxy-androst-4-ene-3,17-dione(14α-OH-AD)is an important precursor for the synthesis of steroid drugs with anticancer and carcinolytic ***,14α-OH-AD was mostly synthesized by whole-cell fermentation of mold fungi using androstenedione(AD)as a substrate,which had difficulties in product isolation and purification as well as problems of high production *** this study,the source of the 14α-hydroxylase gene was *** 14α-hydroxylase genes were heterologously expressed in Mycolicibacterium neoaurum(MNR)M3ΔksdD,which enabled the one-step biotransformation from the cheap substrate phytosterols(PS)to 14α-OH-AD,reducing the difficulty of product purification and production *** is more,to alleviate the problem of poor activity of 14α-hydroxylase,the 14α-hydroxylase gene was co-expressed with the electron transport chain element genes and the coenzyme regeneration genes,and a superior engineered strain MNR M3ΔksdD/pMV261-14α-G6PDH was ***,the transformation conditions were optimized for the transformation of PS by the engineered *** molar yield of 14α-OH-AD reached to 60.4±2.3%(about 0.22 g/L productivity).This study investigated for the first time the effects of the tandem electron transport chain element genes and the tandem coenzyme regeneration genes on the 14α-hydroxylation reaction,providing a theoretical basis for the industrial production of 14α-OH-AD.

关键词： 14α-hydroxy-androst-4-ene-3,17-dione Mycolicibacterium neoaurum 14α-hydroxylase Electron transportation Coenzyme regeneration

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A Novel Variable Selection Algorithm for Soft Sensor Using Gated Recurrent Unit and Garrote Variable Attention Mechanism 42

A Novel Variable Selection Algorithm for Soft Sensor Using G...

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42nd Chinese control Conference, CCC 2023

作者： Sui, Lin Xiong, Weili School of Internet of Things Engineering Jiangnan University Wuxi214122 China Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Wuxi214122 China

ISBN: (纸本)9789887581543

This paper proposed a variable selection algorithm for soft sensor applications using the garrote variable attention mechanism and gated recurrent unit (GRU). Firstly, a well-trained GRU deep neural network is obtained by hyperparameter optimization. Secondly, a set of variable attention coefficients was designed based on the maximal information coefficient and embedded in the nonnegative garrote (NNG) algorithm constraints to overcome the disadvantage of biased coefficient estimation in this algorithm. Finally, the GRU network input weights are sparsely optimized using the optimized NNG algorithm to eliminate redundant variables and simplify the model structure. A numerical simulation case verifies the effectiveness of the proposed algorithm. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Deep neural networks

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Coupling effect of micro-textured tools and cooling conditions on the turning performance of aluminum alloy 6061

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Advances in Manufacturing 2023年第4期11卷 663-681页

作者： Guo-Liang Liu Jin-Tao Zheng Chuan-Zhen Huang Shu-Feng Sun Xin-Fu Liu Long-Jie Dai De-Xiang Wang Xiang-Yu Wang Key Lab of Industrial Fluid Energy Conservation and Pollution Control Ministry of EducationKey Lab of Industrial Fluid Energy Conservation and Pollution ControlMinistry of EducationSchool of Mechanical and Automotive EngineeringQingdao University of TechnologyQingdao266520ShandongPeople’s Republic of China State Key Laboratory of High Performance Complex Manufacturing Central South UniversityChangsha410083People’s Republic of China Key Laboratory of High-Efficiency and Clean Mechanical Manufacture(Ministry of Education) School of Mechanical EngineeringShandong UniversityJinan250061People’s Republic of China School of Mechanical Engineering Yanshan UniversityQinhuangdao066004HebeiPeople’s Republic of China Qingdao Choho Ind Co Ltd Qingdao266705ShandongPeople’s Republic of China School of Mechanical Engineering University of JinanJinan250022People’s Republic of China

Micro-texturing has been widely proven to be an effective technology for achieving sustainable ***,the performance of micro-textured tools under different cooling conditions,especially their coupling effect on machined surface integrity,was scarcely *** this paper,the non-textured,linear micro-grooved,and curvilinear micro-grooved inserts were used to turn aluminum alloy 6061 under dry,emulsion,and liquid nitrogen cryogenic cooling *** coupling effects of different micro-textures and cooling conditions on cutting force,cutting temperature,and machined surface integrity,including the surface roughness,work hardening,and residual stress,were revealed and discussed in *** indicated that the micro-grooved tools,especially the curvilinear micro-grooved tools,not only reduced the cutting force and cutting temperature,but also improved the machined surface *** addition,the micro-grooved tools can cooperate with the emulsion or liquid nitrogen to reduce the cutting force,cutting temperature,and improve the machined surface integrity generally,although the combination of emulsion cooling condition and micro-grooved tools generated negative coupling effects on cutting forces and surface work ***,the combination of curvilinear micro-grooved cutting tools and cryogenic cooling condition resulted in the lowest cutting force and cutting temperature,which generated the surface with low roughness,weak work hardening,and compressive residual stress.

关键词： Micro-grooved cutting tool Cooling condition Cutting force Cutting temperature Surface integrity

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