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第三十九届中国控制会议

作者： Wei Yin Weiqi Qin Xiaowei Jiang Xiangyong Chen Ming Chi School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Affiliated Hospital of Shandong Medical College School of Automation and Electrical Engineering Linyi University Huazhong University of Science and Technology

Neimark-Sacker bifurcation of a delay differential equation modeling two-enterprise interaction mechanism is investigated. For the demands of computer simulation applications, the discrete-time two-enterprise interaction model is proposed by using the forward Euler scheme. By discussing the characteristic equation of linearized part, the local stability criterion of the positive fixed point is presented. Time lag is selected as the bifurcation parameter. Then it is demonstrated that variation of time lag may result in Neimark-Sacker bifurcation. Furthermore, derivations for the directions and stability of Neimark-Sacker bifurcation are also given. Finally, we simulate the main results.

关键词： Leslie-Gower model Delay Stability Neimark-Sacker bifurcation

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Glucose Regulation for Subjects with Type 1 Diabetes Using Active Disturbance Rejection control

Glucose Regulation for Subjects with Type 1 Diabetes Using A...

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第三十八届中国控制会议

作者： Deheng Cai Jiliang Song Junzheng Wang Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

In artificial pancreas(AP) systems, control algorithms play an important role in the blood glucose(BG) *** ability of active disturbance rejection control(ADRC), which can deal with various disturbances, enables it to become a promising approach in the control algorithm design for BG regulation when facing many disturbances(e.g. glucose fluctuation caused by meal intakes and exercises). In this paper, an ADRC controller is proposed for the AP systems. To ensure the safety,the insulin on board(IOB) constraints and the insulin delivery constraints are introduced to the ADRC controller. The controller is evaluated on the FDA-accepted UVA/Padova T1 DM simulator with the 10-adult cohort. For both announced and unannounced meals, the controller achieves satisfactory performance in terms of mean glucose(139.9 mg/dl for announced meals, 157.9 mg/dl for unannounced meals) and percentage time in [70, 180] mg/dl(91.5% for announced meal, 68.9% for unannounced meals)without having the risk of hypoglycemia.

关键词： Glucose Regulation Type 1 Diabetes Artificial Pancreas Active Disturbance Rejection control

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An Efficient Method to Discover Association Rules of Mode-Dependent Alarms Based on the FP-Growth Algorithm

An Efficient Method to Discover Association Rules of Mode-De...

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IEEE Canada Electric Power Conference, EPEC

作者： Kai Ru Wang Wenkai Hu Tongwen Chen University of Alberta Edmonton Alberta T6G 1H9 Canada School of Automation and Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan China

ISBN: (数字)9781728164892

ISBN: (纸本)9781728164908

State-based alarming is an advanced technique to reduce nuisance alarms and alarm floods by suppressing alarms associated with certain conditions or operating modes. To implement this technique, the key is to find the associations between operating modes and alarms. In practice, this is mainly done based on the experience of plant operators and expert knowledge of process engineers, and thus is very time consuming. Therefore, this paper proposes a data driven method to discover the association rules of mode-dependent alarms for both single and multiple operating modes from the historical Alarm and Event (A&E) logs in an efficient way based on a data mining approach named FP-Growth. The effectiveness of the proposed method is demonstrated by an industrial case study.

关键词： Data mining Databases Alarm systems Power systems Conferences Systematics Standards

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Optimal Blood Glucose Prediction based on Intermittent Data from Wearable Glucose Monitoring Sensors

Optimal Blood Glucose Prediction based on Intermittent Data ...

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第三十八届中国控制会议

作者： Lijun Hou Huipeng Zhang Junzheng Wang Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

Blood glucose prediction is to predict the glucose trend over time based on historical glucose data, and it plays a crucial role in the closed-loop control of artificial pancreas, which can reduce the risk of complications by regulating insulin dose and injection time. This paper proposes a Kalman-filter-based glucose prediction method through minimizing the mean square prediction error, which assumes that the data is sampled every 15 min from a wearable flash glucose monitoring sensor. This method calculates glucose estimates every 5 min and provides glucose predictions for the next 30 min. The method is evaluated on in-silico data generated from the 10-adult cohort of the US FDA-accepted UVA/Padova T1 DM simulator. The predicted results are compared with CGM data with 5-min sample-period through multiple metrics, including the mean square prediction error and the mean absolute relative deviation. The results show that the performance of the proposed approach with slow-rate glucose data(15 min) is close to that obtained based on fast-rate data(5 min).

关键词： Blood Glucose Prediction Wearable Devices Mean Square Prediction Error Sampled Data Kalman Filtering

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Distributed stochastic proximal algorithm with random reshuffling for non-smooth finite-sum optimization

arXiv

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arXiv 2021年

作者： Jiang, Xia Zeng, Xianlin Sun, Jian Chen, Jie Xie, Lihua Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China School of Electronic and Information Engineering Tongji University Shanghai200082 China Ministry of Education Beijing100081 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore

The non-smooth finite-sum minimization is a fundamental problem in machine learning. This paper develops a distributed stochastic proximal-gradient algorithm with random reshuffling to solve the finite-sum minimization over time-varying multi-agent networks. The objective function is a sum of differentiable convex functions and non-smooth regularization. Each agent in the network updates local variables by local information exchange and cooperates to seek an optimal solution. We prove that local variable estimates generated by the proposed algorithm achieve consensus and are attracted to a neighborhood of the optimal solution with an (formula presented) convergence rate, where T is the total number of iterations. Finally, some comparative simulations are provided to verify the convergence performance of the proposed algorithm. © 2021, CC BY.

关键词： Optimal systems

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A Blockchain-based Framework for Collaborative Production in Distributed and Social Manufacturing

A Blockchain-based Framework for Collaborative Production in...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Ouyang, Liwei Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Qingdao Academy of Intelligent Industries Qingdao266109 China

ISBN: (纸本)9781728128535

In recent years, novel collaborative production paradigms, such as (re-)distributed manufacturing and social manufacturing, have attracted intensive attention due to their potential of further changing the existing manufacturing modes and industrial structures. Blockchain, as a new distributed computing architecture, is expected to be successfully used in manufacturing, and help solve issues related to interoperability and collaboration, security and supervision, marketization and protocol, democratic organization and global value chain governance, and so on. In this paper, a blockchain-based framework for collaborative production is proposed, aiming at providing novel ideas for the design, implementation and optimization of collaborative production, and also inspiring the upgrading and transformation of manufacturing industries. © 2019 IEEE.

关键词： Smart contract

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Local Smooth Path Planning for Turning Around in Narrow Environment

Local Smooth Path Planning for Turning Around in Narrow Envi...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Xiaohui Tian Mengyin Fu Yi Yang Meiling Wang Dongyu Liu State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (纸本)9781728136677

In this paper, we introduce a local smooth path planning algorithm for turning around in narrow environment. The algorithm uses a combination of the minimum turning radius arc and the Bezier curve to generate a near optimal smoothing turn-around path in narrow roads or cluttered environments. The algorithm will generate a smooth trajectory that conforms to the kinematic constraints of unmanned ground vehicle (UGV), by adjusting the heading to the target angle through several minimum-radius turns, and smoothly connecting to the global reference path via Bezier curve. We analyze the surrounding congestion and narrowness to choose appropriate turn-around area by integrating obstacle distribution and road edges before path planning. The algorithm was tested at IN 2 BOT UGV in our campus and 2018 Cross Dangers & obstacles. The experimental results indicated that the algorithm works efficiently with our previous work and shows good performance in accuracy and computational time.

关键词： Turning Roads Trajectory Planning Kinematics Land vehicles

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K-9 Artificial Intelligence Education in Qingdao: Issues, Challenges and Suggestions

K-9 Artificial Intelligence Education in Qingdao: Issues, Ch...

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IEEE International Conference on Networking, Sensing and control

作者： Xiaoyan Gong Ying Tang Xiwei Liu Sifeng Jing Wei Cui Joleen Liang Fei-Yue Wang The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao China Rowan University Glassboro NJ USA Squirrel AI Learning Shanghai China

ISBN: (数字)9781728168555

ISBN: (纸本)9781728168562

Nowadays, AI education from Kindergarten to 9 th grade(K-9) is in full swing in China, but many challenges exist, such as fragmented AI curricula, ineffective teaching tools, and uneven educational resources in urban and rural areas, etc. So this paper presents an in-depth study of the current status of K-9 AI education in Qingdao area through questionnaires, expert discussions, and field visits to sort out existing problems and then put forward corresponding advice and suggestions. Collected data is then analyzed from the perspectives of government, schools, teachers, students and parents, respectively. Results show that AI-related educational activities have been carried out in Qingdao area to improve students' AI literacy. But efforts are still needed to make such education more systematic, standardized, and personalized. Finally the paper made a list of recommendations corresponding to these needed efforts.

关键词： Ethics Systematics Education Government Tools Sensors Artificial intelligence

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A Parallel Education Based intelligent Tutoring systems Framework

A Parallel Education Based Intelligent Tutoring Systems Fram...

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IEEE International Conference on Networking, Sensing and control

作者： Sifeng Jing Ying Tang Xiwei Liu Xiaoyan Gong Wei Cui Joleen Liang The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao China Rowan University Glassboro NJ USA Squirrel AI Learning Shanghai China

ISBN: (数字)9781728168555

ISBN: (纸本)9781728168562

although online education has improved efficiency of learners' access to high-quality educational resources, real-time interaction between instructors and learners have not yet been achieved in online personalized learning. intelligent Tutoring systems (ITS) provides a feasible way to realize realtime personalized learning guidance and resource recommendations by applying AI to capture and analyze online learners' characteristics and behaviors. In this paper, reviews and trends of ITS are discussed and three challenges of ITS research & development are pointed out: learner model, guidance mechanism and human-computer interaction mechanism. In order to address these issues, parallel intelligence theory is introduced and a parallel intelligence education based ITS framework is proposed.

关键词： Human computer interaction Conferences Education Market research Sensors Artificial intelligence

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Applications of Evolutionary Computation and Artificial Intelligence in Metallurgical Industry

Applications of Evolutionary Computation and Artificial Inte...

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General Conference on Emerging Arts of Research on Management and Administration, GEAR 2018

作者： An, Jianqi She, Jinhua Chen, Huicong Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Engineering Tokyo University of Technology Tokyo192-0982 Japan

ISBN: (纸本)9789811369353

Metallurgical industry is one of the most important industrial processes, which mainly consists of coking process, sintering process, ironmaking process, and casting and rolling process. All of the metallurgical processes are complex, multivariate and nonlinear systems with large time-delay. Some chemical or physical mechanisms are even not clear and uncertain. It is difficult to establish the models, design the controllers, devise the scheduling and optimization strategies, and make the operation decisions by the conventional mechanism-based methods. Nevertheless, these processes work continuously and repetitively, which produces large amounts of data, and consists of lots of knowledge and expert experiences. In the last decade, evolutionary computation and artificial intelligence (ECAI) began to be widely used in metallurgical industry and many good results were reported. This letter demonstrates how the development of ECAI impacts the metallurgical industry by analyzing some good applications of the ECAI in typical metallurgical processes and discusses the future development trends and challenges of the applications of the ECAI in metallurgical industries. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Sintering

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