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IEEE Transactions on Intelligent Vehicles 2023年第2期9卷 3220-3231页

作者： Xiao Wang Ke Tang Xingyuan Dai Jintao Xu Quancheng Du Rui Ai Yuxiao Wang Weihao Gu Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei China Haomo Technology Company Ltd. Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying social characteristics among humans. To effectively assess the risks prevailing in the vicinity of AVs in social interactive traffic scenarios and achieve safe autonomous driving, this article proposes a social-suitable and safety-sensitive trajectory planning (S $^{\text{4}}$ TP) framework. Specifically, S $^{\text{4}}$ TP integrates the Social-Aware Trajectory Prediction (SATP) and Social-Aware Driving Risk Field (SADRF) modules. SATP utilizes Transformers to effectively encode the driving scene and incorporates an AV's planned trajectory during the prediction decoding process. SADRF assesses the expected surrounding risk degrees during AVs-HDVs interactions, each with different social characteristics, visualized as two-dimensional heat maps centered on the AV. SADRF models the driving intentions of the surrounding HDVs and predicts trajectories based on the representation of vehicular interactions. S $^{\text{4}}$ TP employs an optimization-based approach for motion planning, utilizing the predicted HDVs' trajectories as input. With the integration of SADRF, S $^{\text{4}}$ TP executes real-time online optimization of the planned trajectory of AV within low-risk regions, thus improving the safety and the interpretability of the planned trajectory. We have conducted comprehensive tests of the proposed method using the SMARTS simulator. Experimental results in complex social scenarios, such as unprotected left-turn intersections, merging, cruising, and overtaking, validate the superiority of our proposed S $^{\text{4}}$ TP in terms of safety and rationality. S $^{\text{4}}$ TP achieves a pass rate of 100% across all scenarios, surpassing the current state-of-the-art methods Fanta of 98.25% and Predictive-Decision of 94.75%.

关键词： Trajectory Safety Vehicles Trajectory planning Autonomous vehicles Risk management Behavioral sciences

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Generalized Zeroing Neural Network Model for Online Solving Time-Varying Cube Roots with Various External Disturbances in Different Domain

SSRN

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SSRN 2022年

作者： Wang, Gang Liu, Yongbai Sun, Yingyi Yu, Junzhi Sun, Zhongbo Department of Mechatronic Engineering Changchun University of Technology Changchun130012 China College of Economics and Management Jilin Agricultural University Changchun130118 China State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering Science BIC-ESAT College of Engineering Peking University Beijing100871 China Department of Control Engineering Changchun University of Technology Changchun130012 China

As a basic problem of the nonlinear dynamic model, the online solution of time-varying cube root problem (TVCRP) is widely used in science and engineering. However, the practical system is frequently disturbed by the external factors, which inevitably leads to unknown disturbances in the solution process. Therefore, addressing the TVCRP with high accuracy in non-ideal environment (unknown disturbances) is the basis of solving the nonlinear dynamic model. In this work, a noise-suppression zeroing neural dynamics (NSZND) model is investigated and developed from the control perspective to resolve the time-varying or time-invariant cube root problem (TV/TICRP) under the different disturbances (bounded and unbounded disturbances) in © 2022, The Authors. All rights reserved.

关键词： Dynamic models

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Cooperative robust output regulation for second-order nonlinear multi-agent systems with an unknown exosystem

Cooperative robust output regulation for second-order nonlin...

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IEEE Annual Conference on Decision and control

作者： Yi Dong Jie Chen Jie Huang Department of Automation Chinese University of Hong Kong Shatin N.T. Hong Kong State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Department of Mechanical and Automation Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong

The cooperative robust output regulation problem for a class of second-order nonlinear multi-agent systems with an exactly known exosystem has been studied recently. This paper further studies the same problem for a class of second-order nonlinear multi-agent systems subject to an unknown exosystem. We first show that the problem can be converted into the adaptive stabilization problem for a modified augmented system composed of the given multi-agent system and the distributed internal model. Due to the uncertain parameter in the exosystem, the augmented system is a nonlinear multi-input system with both dynamic and static uncertainties. By combining the adaptive control technique and the robust control technique, we solve our problem by a distributed adaptive robust state feedback controller.

关键词： Multi-agent systems Mathematical model Robustness Robust control Automation Electronic mail Nickel

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Blockchain-based Social Manufacturing for Customization Production

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IFAC-PapersOnLine 2020年第5期53卷 53-58页

作者： Xiuqin Shang Xi Chen Lulu Niu Gang Xiong Zhen Shen Xisong Dong Zhengchao Shen Chao Liu Bangwen Xi the Research Center of Precision Sensing and Control the state key laboratory for management and control of complex systems & Beijing engineering research center of intelligent systems and technology institute of automation Chinese Academy of Sciences Beijing 100190 China Beijing University of Posts and Telecommunications Beijing 100876 China Alstom Beizhong Power (Beijing) Co. Ltd. Beijing 100040 China the System Integration Electronics (Hangzhou)Co. LTD No. 58 No. 11 Road Foxconn Qiantang Tech-Industrial Area HETZ Hangzhou 310018 China

This paper proposes the social manufacturing based on Blockchain, which realizes precise and efficient customization through smart contract and distributed accounting. It is a new manufacturing mode of service-oriented, distributed and collaborative customization. This paper proposes the definition of SM based on Blockchain. In the process of using to Blockchain, it can form a strong trust relationship, so that multiple nodes / roles in SM can save the complete copy of the whole database, rather than a centralized permission / role. Secondly, the Blockchain-based SM system is developed for customized manufacturing. Finally, its application case and the optimization results are given. In SM, it is the key that how to transform customized manufacturing actions into socialized actions of manufacturing resources through internet communities and interconnect Socialized Manufacturing Resources (SMRs) in upstream and downstream. In this paper, the smart contract relationship is established based on Blockchain between SMRs to build credit mechanism in SM, Which can ensure the effective circulation and association of SMRs.

关键词： Social Manufacturing Blockchain Optimization SM Resources

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Analyzing the Evolutionary Characteristics of the Cluster of COVID-19 under Anti-contagion Policies

Analyzing the Evolutionary Characteristics of the Cluster of...

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IEEE International Conference on Intelligence and Security Informatics, ISI

作者： Pu Miao Hu Tian Xingwei Zhang Saike He Xiaolong Zheng Desheng Dash Wu Daniel Zeng The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Stockholm Business School Stockholm University Stockholm Sweden

ISBN: (数字)9781728188003

ISBN: (纸本)9781728188010

With the rampaging of Coronavirus disease 2019 (COVID-19) across the world, analyzing the dynamic characteristics and understanding the evolutionary patterns of clusters are becoming even more crucial for people and policymakers to make timely responses for avoiding injury caused by COVID-19. To solve the scarcity of the fine-grained spatiotemporal data, we construct a novel dataset about the spread of patients during the resurgent period of the COVID-19 epidemic at the Xinfadi Market in Beijing. Leveraging our self-build dataset, we analyze the evolutionary characteristics of the cluster of COVID-19 under anti-contagion policies and obtained some remarkable evolution patterns. These findings can provide significant insights for policymakers and researchers to understand the evolutionary characteristics regarding the cluster of COVID-19 and deploy effective anti-contagion policies.

关键词： COVID-19 Epidemics Simulation Sociology Market research Spatiotemporal phenomena Statistics

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Parameter identification of plant growth models with stochastic development

Parameter identification of plant growth models with stochas...

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International Conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Applications (FSPMA)

作者： Mengzhen Kang Jing Hua Philippe de Reffye Marc Jaeger Qingdao Academy of Intelligent Sciences Qingdao China State Key Laboratory of Management and Control for Complex Systems CASIA Beijing China AMAP Unit CIRAD Montpellier Languedoc-Roussillon FR AMAP Unit CIRAD Montpellier Languedoc-Roussillon France LIRMM ICAR University of Montpellier France

ISBN: (纸本)9781509016600

Plant architectures generally display structural variations among individuals. Stochastic FSPMs have been developed to capture such feature, but calibrating such models is a challenging issue. For GreenLab model, parameter identification has been achieved on several crops and trees, but the estimation of functional parameters is mostly limited to plants with deterministic development. In this work, we propose a methodological framework allowing the efficient FSPM parameter estimation for stochastic ramified plants. We focus on the randomness in three kinds of meristem activities in plant development: growth, death and branching. Concepts of organic series and potential structure are introduced to build the fitting target as well as corresponding model output. We show that, with a limited set of sampled plants (here from simulation), using a few organic series, the inverse method retrieves well the parameter values (the original parameter set being known here). Requiring the concept of physiological age and the assumption of common biomass pool, the proposed approach provides a solution of solving source-sink functions of complex plant architectures, with a novel simplified way of plant sampling. The proposed parameter estimation frame is promising, since this in silico process mimics the procedure of calibrating model for real plants in a stand. Estimating parameters on stochastic plant architectures opens a new range of coming applications.

关键词： Stochastic processes Biological systems Physiology Biological system modeling Computational modeling Vegetation Biomass

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Raunet: Residual attention u-net for semantic segmentation of cataract surgical instruments

arXiv

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arXiv 2019年

作者： Ni, Zhen-Liang Bian, Gui-Bin Zhou, Xiao-Hu Hou, Zeng-Guang Xie, Xiao-Liang Wang, Chen Zhou, Yan-Jie Li, Rui-Qi Li, Zhen University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Cas Center for Excellence in Brain Science and Intelligence Technology Beijing100190 China

Semantic segmentation of surgical instruments plays a cru-cial role in robot-assisted surgery. However, accurate segmentation of cataract surgical instruments is still a challenge due to specular reec-tion and class imbalance issues. In this paper, an attention-guided net-work is proposed to segment the cataract surgical instrument. A new at-tention module is designed to learn discriminative features and address the specular reection issue. It captures global context and encodes se-mantic dependencies to emphasize key semantic features, boosting the feature representation. This attention module has very few parameters, which helps to save memory. Thus, it can be exibly plugged into other networks. Besides, a hybrid loss is introduced to train our network for addressing the class imbalance issue, which merges cross entropy and logarithms of Dice loss. A new dataset named Cata7 is constructed to evaluate our network. To the best of our knowledge, this is the first cataract surgical instrument dataset for semantic segmentation. Based on this dataset, RAUNet achieves state-of-the-art performance 97.71% mean Dice and 95.62% mean IOU. Copyright © 2019, The Authors. All rights reserved.

关键词： Surgical equipment

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Coordinated control strategy of wind/battery energy storage system hybrid power output based on adaptive dynamic programming

Coordinated control strategy of wind/battery energy storage ...

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World Congress on Intelligent control and Automation (WCICA)

作者： Xiangjun Li Jingqiong Zhang Yuting He Dongbin Zhao Electrical Engineering and New Material Department China Electric Power Research Institute Beijing China School of Electrical and Electronic Engineering North China Electric Power University Beijing China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781467384155

Based on the rate control method of the wind power fluctuation, this paper proposes an adaptive dynamic programming (ADP) based method to optimize the power of battery energy storage systems (BESS) adaptively. On the one hand, this method can be used to adjust the unstable wind and BESS hybrid power output so as to satisfy the requirements of wind power. On the other hand, this method can be used to control the battery state of charge (SOC) maintained within a suitable range, to achieve a reasonable charge and discharge function of the battery. Take a typical wind farm's output as example, under the limitation of wind power volatility and battery state of charge, this paper shows the experiment that through the real-time online optimization of the smoothing process. The simulation results show the effectiveness and feasibility of the proposed coordinated control strategy based on ADP.

关键词： Hybrid power systems Wind power generation Fluctuations Batteries state of charge Discharges (electric)

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A Robust Road Segmentation Method Based on Graph Cut with Learnable Neighboring Link Weights

A Robust Road Segmentation Method Based on Graph Cut with Le...

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17th International IEEE Conference on Intelligent Transportation systems & The Asia-Pacific Council on systems Engineering Conference 2014

作者： Jun Yuan Shuming Tang Fei Wang Hong Zhang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences High-Tech Innovation Engineering Center Institute of AutomationChinese Academy of Sciences Institute of Artificial Intelligence and Robotics of Xi'an Jiaotong University School of Information Engineering Minzu University of China

Road region detection is a crucial functionality for road following in advanced driver assistance systems(ADAS).To address the problem of environment interference in road segmentation through a monocular vision approach,a novel graph-cut based method is proposed in this *** novelty of this proposal is that weights of neighboring links(n-links) in a s-t graph are estimated by Multilayer Perceptrons(MLPs) rather than calculating by the neighboring contrast simply in previous graph-cut based *** n-link weights by MLPs reinforces the ability of graph-cut based road segmentation algorithms to tolerate the complex and changeable appearance of road ***,the Gentle Ada Boost algorithm is integrated into the graph-cut framework to estimate the terminal link(t-link) weights in the s-t *** are conducted to show the robustness and efficiency of the proposed method.

关键词： image A Robust Road Segmentation Method Based on Graph Cut with Learnable Neighboring Link Weights Graph

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Adaptive critic designs for solving event-based H∞ control problems

Adaptive critic designs for solving event-based H∞ control ...

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American control Conference

作者： Ding Wang Chaoxu Mu Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China the School of Electrical and Information Engineering Tianjin University Tianjin 300072 China the School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing 100083 China

ISBN: (纸本)9781509045839

In this paper, the adaptive critic method is applied to solve a class of continuous-time event-based H_∞ control problems. The present control problem is transformed into a two-player zero-sum differential game and the adaptive critic structure is employed for coping with the event-based minimax optimization. Next, the event-based optimal feedback control and the time-based worst-case disturbance law are learned by training a critic neural network. In addition, the closed-loop system is constructed with stability analysis of the critic error dynamics and the sampled-data plant. The exclusion of the infamous Zeno behavior of the present event-based control design is also discussed. Finally, the control performance of the present approach is evaluated through simulation study.

关键词： exclusion infamous Zeno exclusion critic Event-based Data sampling control performance design control

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