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arXiv 2023年

作者： Yu, Xian Fang, Xiaozhu Mu, Biqiang Chen, Tianshi School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

For data-driven iterative learning control (ILC) methods, both the model estimation and controller design problems are converted to parameter estimation problems for some chosen model structures. It is well-known that if the model order is not chosen carefully, models with either large variance or large bias would be resulted, which is one of the obstacles to further improve the modeling and tracking performances of data-driven ILC in practice. An emerging trend in the system identification community to deal with this issue is using regularization instead of the statistical tests, e.g., AIC, BIC, and one of the representatives is the so-called kernel-based regularization method (KRM). In this paper, we integrate KRM into data-driven ILC to handle a class of repetitive linear time-varying systems, and moreover, we show that the proposed method has ultimately bounded tracking error in the iteration domain. The numerical simulation results show that in contrast with the least squares method and some existing data-driven ILC methods, the proposed one can give faster convergence speed, better accuracy and robustness in terms of the tracking performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Model structures

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A Test Suite and An Optimizer for Dietary Nutrition Optimization Problem: From Constrained Many-Objective Perspective

A Test Suite and An Optimizer for Dietary Nutrition Optimiza...

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2023 IEEE Congress on Evolutionary Computation, CEC 2023

作者： Ti, Yaqi Li, Changhe Yang, Shengxiang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

ISBN: (纸本)9798350314588

With increasing people who suffer from diet-related diseases, providing suggestions for personal daily nutrient-dense intake is highly expected. However, current dietary nutrition models are less precise, and dietary nutrition optimizers usually fail to give satisfactory solutions. Therefore, we construct a constrained many-objective nutrition model with more precise nutrient assessments and a scalable constrained many-objective benchmark set. This test suite has great flexibility in evaluating algorithms' performance on high dimensional search and objective spaces with some feasible region fragments. We also propose a kd-tree based dynamic constrained many-objective evolutionary algorithm to search for customized food combinations according to personal daily consumption and intake preference. Experiments show that our algorithm has better diversity maintenance ability in high dimension space. © 2023 IEEE.

关键词： Nutrition

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DeepDir: a deep learning approach for API directive detection

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science China(Information sciences) 2021年第9期64卷 238-240页

作者： Jingxuan ZHANG He JIANG Shuai LU Ge LI Xin CHEN College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics State Key Laboratory for Novel Software Technology Nanjing University Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education School of Software Dalian University of Technology School of Electronic Engineering and Computer Science Peking University School of Computer Science and Technology Hangzhou Dianzi University

Dear editor,Software developers tend to reuse existing libraries to facilitate their development process and implement certain functionalities by invoking application programming interfaces(APIs) [1]. However, it remains a challenging task for developers to correctly use APIs [2], so they often consult API learning resources [3, 4]. As one of the most important API learning resources,

关键词： API Specification API Directive Deep Learning Text Classification Imbalanced Learning

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Electro-optical phase-locked loop for hybrid integrated external cavity laser

Electro-optical phase-locked loop for hybrid integrated exte...

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2023 Optical Fiber Communications Conference and Exhibition, OFC 2023

作者： Liu, Chuxin Guo, Yuyao Xu, Ruiyang Lu, Liangjun Chen, Jianping Zhou, Linjie Shanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Lab of Navigation and Location Services Shanghai Institute for Advanced Communication and Data Science Department of Electronic Engineering Shanghai200240 China SJTU-Pinghu Institute of Intelligent Optoelectronics Pinghu314200 China

We implement an analog EO-PLL for a III/V-Si3N4 hybrid integrated ECL to generate a highly-linear FMCW signal over multiple wavelengths. The ranging resolution is improved from 5 m to 35 cm for a 100-m target. © ... 详细信息

ISBN: (纸本)9781957171180

关键词： Phase locked loops

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Molecular dynamics simulations of ovalbumin adsorption at squalene/water interface

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Chinese Journal of Chemical Engineering 2022年第10期50卷 369-378页

作者： Qingxia Xiong Ying Ren Yufei Xia Guanghui Ma Reiji Noda Wei Ge State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China Division of Environmental Engineering Science Graduate School of Science and TechnologyGunma University1-5-1 Tenjin-choKiryuGunma 376-8515Japan State Key Laboratory of Biochemical Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China Innovation Academy for Green Manufacture Chinese Academy of SciencesBeijing 100190China

The adsorption of protein molecules to oil/water(O/W)interface is of critical importance for the product design in a wide range of technologies and industries such as biotechnology,food industry and pharmaceutical *** this work,with ovalbumin(OVA)as the model protein,the adsorption conformations at the O/W interface and the adsorption stability have been systematically studied via multiple simulation methods,including all-atom molecular dynamic(AAMD)simulations,coarse-grained molecular dynamic(CGMD)simulations and enhanced sampling *** computational results of AAMD and CGMD show that the hydrophobic tail of OVA tends to be folded under long time relaxation in aqueous phase,and multiple adsorption conformations can exist at the interface due to heterogeneous interactions raising from oil and water *** further study the adsorption sites of the protein,the adsorption kinetics of OVA at the O/W interface is simulated using metadynamics method combined with CGMD simulations,and the result suggests the existence of multiple adsorption conformations of OVA at interface with the head-on conformation as the most stable *** all,this work focuses on the adsorption behaviors of OVA at squalene/water interface,and provides a theoretical basis for further functionalization of the proteins in emulsion-based products and engineering.

关键词： Molecular dynamicssimulation Metadynamics Protein adsorption Structural stability Ovalbumin

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Assimilation of ASCAT Sea Surface Wind Retrievals with Correlated Observation Errors

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Journal of Meteorological Research 2021年第3期35卷 478-489页

作者： Boheng DUAN Weimin ZHANG Xiaofeng YANG Mengbin ZHU College of Meteorology and Oceanology National University of Defense TechnologyChangsha 410073 Laboratory of Software Engineering for Complex Systems Changsha 410073 State Key Laboratory of Remote Sensing Science Chinese Academy of SciencesBeijing 100101 Hainan Key Laboratory of Earth Observation Sanya 572029 Beijing Institute of Applied Meteorology Beijing 100029

data assimilation systems usually assume that the observation errors of wind components, i.e., u(the longitudinal component) and v(the latitudinal component), are uncorrelated. However, since wind components are derived from observations in the form of wind speed and direction(spd and dir), the observation errors of u and v are correlated. In this paper, an explicit expression of the observation errors and correlation for each pair of wind components are derived based on the law of error propagation. The new data assimilation scheme considering the correlated error of wind components is implemented in the Weather Research and Forecasting data Assimilation(WRFDA) system. Besides, adaptive quality control(QC) is introduced to retain the information of high wind-speed observations. Results from real data experiments assimilating the Advanced Scatterometer(ASCAT) sea surface winds suggest that analyses from the new data assimilation scheme are more reasonable compared to those from the conventional one, and could improve the forecasting of Typhoon Noru.

关键词： data assimilation Advanced Scatterometer(ASCAT) wind components correlated observation error

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Towards robust neural networks via a global and monotonically decreasing robustness training strategy

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Frontiers of Information Technology & Electronic Engineering 2023年第10期24卷 1375-1389页

作者： Zhen LIANG Taoran WU Wanwei LIU Bai XUE Wenjing YANG Ji WANG Zhengbin PANG Institute for Quantum Information&State Key Laboratory of High Performance Computing National University of Defense TechnologyChangsha 410073China State Key Laboratory of Computer Science Institute of Software Chinese Academy of SciencesBeijing 100190China School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 100190China College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China Key Laboratory of Software Engineering for Complex Systems National University of Defense TechnologyChangsha 410073China

Robustness of deep neural networks(DNNs)has caused great concerns in the academic and industrial communities,especially in safety-critical *** of verifying whether the robustness property holds or not in certain neural networks,this paper focuses on training robust neural networks with respect to given ***-of-the-art training methods,interval bound propagation(IBP)and CROWN-IBP,perform well with respect to small perturbations,but their performance declines significantly in large perturbation cases,which is termed“drawdown risk”in this ***,drawdown risk refers to the phenomenon that IBPfamily training methods cannot provide expected robust neural networks in larger perturbation cases,as in smaller perturbation *** alleviate the unexpected drawdown risk,we propose a global and monotonically decreasing robustness training strategy that takes multiple perturbations into account during each training epoch(global robustness training),and the corresponding robustness losses are combined with monotonically decreasing weights(monotonically decreasing robustness training).With experimental demonstrations,our presented strategy maintains performance on small perturbations and the drawdown risk on large perturbations is alleviated to a great *** is also noteworthy that our training method achieves higher model accuracy than the original training methods,which means that our presented training strategy gives more balanced consideration to robustness and accuracy.

关键词： Robust neural networks Training method Drawdown risk Global robustness training Monotonically decreasing robustness

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An LMI approach to design robust fault detection filter for uncertain Lur'e singularly perturbed systems

An LMI approach to design robust fault detection filter for ...

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第43届中国控制会议

作者： Lei Liu Wenjie Dou Ying Yang Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of Technology State Key Lab for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of EngineeringPeking University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In this paper, the robust fault detection filter(RFDF) design problem for uncertain Lur'e singularly perturbed systems(SPSs) with unknown inputs is studied. Firstly, an optimal residual generator is constructed as a reference model, and the design of the RFDF for the system is formulated as an H∞ model matching problem. Secondly, based on the linear matrix inequality(LMI) theory, the sufficient conditions for the augmented system to be absolutely stable and satisfy the H∞ performance index are derived. Then an algorithm is proposed to solve the optimization problem, based on this, the specific parameters of the RFDF are obtained by using the LMI toolbox, and the fault detection method based on residual signal is obtained. Finally, a numerical example is given to verify the feasibility and effectiveness of the proposed results.

关键词： Lur'e Singularly Perturbed systems Fault detection filter Model matching H∞ optimization Linear matrix inequality(LMI)

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Zero-Sum Differential Game-Based Fault-Tolerant Tracking Control for Nonlinear systems With Multiplicative Failures

Zero-Sum Differential Game-Based Fault-Tolerant Tracking Con...

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2022 Chinese Automation Congress, CAC 2022

作者： Tan, Cong Lin, Mingduo Xia, Hongbing Zhao, Bo Xu, Yancai School of Systems Science Beijing Normal University Beijing100875 China Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781665465335

A novel fault-tolerant tracking control (FTTC) approach for affine nonlinear systems is developed from the perspective of zero-sum differential games (ZSDG) to deal with unknown multiplicative actuator failures in this paper. By regarding the control input and the multiplicative actuator failure as two players of a zero-sum game, a performance index function reflecting the trajectory tracking error, the control policy and the unknown failure is established. To handle the tracking Hamilton-Jacobi-Isaacs (HJI) equation associated with the established performance index function, a critic neural network is utilized. Then, the Nash equilibrium solution can be obtained, and the FTTC is achieved. The stability of the faulty nonlinear system is examined through Lyapunov-based approach. Finally, simulation results of a spring system is provided to ensure the utility and the realizability of the ZSDG-based FTTC approach. © 2022 IEEE.

关键词： Nonlinear systems

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data-Driven Human-Robot Interaction Without Velocity Measurement Using Off-Policy Reinforcement Learning

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 47-63页

作者： Yongliang Yang Zihao Ding Rui Wang Hamidreza Modares Donald C.Wunsch Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education School of Automation&Electrical EngineeringUniversity of Science and Technology BeijingBeijing 100083China School of Automation Beijng Institute TechnologyBeijing 100081China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Mechanical Engineering Department Michigan State UniversityEast LansingMI 48824 USA Department of Electrical&Computer Engineering Missouri University of Science&TechnologyRollaMO 65401 USA

In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the *** presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller *** task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop,while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the ***-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance *** the inner-loop,a velocity-free filter is designed to avoid the requirement of end-effector velocity *** this basis,an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task *** simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.

关键词： Adaptive impedance control data-driven method human-robot interaction(HRI) reinforcement learning velocity-free

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