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ieee International symposium on Parallel and Distributed Processing with Applications and ieee International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Xiongjie Tao Hui Guo Caixu Xu Hubei Normal University Huangshi China Guangzhou ForceControl-Yuanhai IT Co. Ltd Guangdong China Faculty of Arts and Humanities Macao University of Science and Technology Macao China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China

With the development of artificial intelligence and the deep integration of digitalization and intelligent manufacturing. Aiming at the “raw material storage yard for raw material preparation in cement manufacturing” which still adopts the traditional manual control method for production, the realization of the digital storage yard not only improves the production efficiency, reduces the production cost of the enterprise, but also improves the working environment of the employees. Therefore, this paper uses IIoT technology and PLC control technology to digitally transform the site, and uses three-dimensional visualization technology to realize the simulation of intelligent equipment in the yard, and at the same time improves the security protection of production data. The realization shows that the remote control scheme of the digital yard based on the IIoT proposed in this paper is of great significance for the enterprise to realize the goal of intelligent, digital and safe production.

关键词： Solid modeling computational modeling Process control Production Raw materials Data models Manufacturing

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Translation of Time Series Data from controlled DC Motors using Disentangled Representation Learning

Translation of Time Series Data from Controlled DC Motors us...

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ieee symposium Series on computational intelligence (SSCI)

作者： Hiba Arnout Johanna Bronner Johannes Kehrer Thomas Runkler Technical University of Munich Munich Germany Siemens AG Munich Germany Siemens AG Technical University of Munich Munich Germany

ISBN: (纸本)9781728190495

In this paper, we consider the problem of translating time series of one controlled DC motor to imitate time series from another motor. Our main goal is to test different controllers and find the best performing controller for a motor operating in the field without knowing its mathematical model. By means of representation disentanglement, we present a new approach that splits the time series of each control system into two representation vectors: a first vector depicting the motor characteristics and its operating mode and a second vector describing the controller effect. We test our method on a scenario where we simulate the behavior of two different controlled DC motors. We map the behavior of a controller of a lab motor to a field motor. The experiments show that DR-TiST can recognize motor and controller characteristics and predict the right behavior.

关键词： Representation learning Time series analysis Velocity control DC motors control systems Mathematical models Noise measurement

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Applying Context State Machines to Smart Elevators: Design, Implementation and Evaluation

Applying Context State Machines to Smart Elevators: Design, ...

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ieee symposium Series on computational intelligence (SSCI)

作者： Songhui Yue Randy K. Smith University of Alabama Tuscaloosa AL USA Global Payments Inc. Atlanta GA

ISBN: (纸本)9781728190495

Current context-aware computing still lacks good representation models, particularly in modeling for proactive decision making in the era of Ubiquitous Computing and the Internet of Things (IoT), To mitigate this issue, we proposed a state-based model of context in our prior research. Based on the model, we introduced Context State Machines (CSM) for simulating state changes of context attribute, situation, and context, which imply contextual behaviors that are often overlooked while very important to context reasoning and system decisions. This research applies CSMs to a real-world context-aware problem from the literature: a smart elevator control system. We introduce the design and implementation of a CSM engine, evaluate the CSM engine by utilizing two context-aware scenarios of the smart elevator, and show that the model can help automatically capture and reason the context without the inference from the developers. To the best of our knowledge, it is the first time in the literature about applying the state-based context modeling approach and the CSM engine to a real-world context-aware application.

关键词： Context-aware services computational modeling Decision making control systems Elevators Cognition Internet of Things

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Quantized synchronization of memristive neural networks with time-varying delays via super-twisting algorithm

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NEUROCOMPUTING 2020年 380卷 133-140页

作者： Sun, Bo Wen, Shiping Wang, Shengbo Huang, Tingwen Chen, Yiran Li, Peng Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu 611731 Peoples R China Huazhong Univ Sci & Technol Sch Automat & Artificial Intelligence Wuhan 430074 Peoples R China Texas A&M Univ Qatar Sci Program Doha 23874 Qatar Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

In this paper, we investigate quantized synchronization control problem of memristive neural networks (MNNs) with time-varying delays via super-twisting algorithm. A feedback controller is introduced with quantized method. To enormously reduce the computational complexity of the controller under super-twisting algorithm, two quantized control schemes are proposed with uniform quantizer and logarithmic quantization. We obtain some sufficient conditions of specific control plans to guarantee that the driving MNNs can synchronize with the response MNNs. A neoteric Lyapunov functional is designed to analyze the synchronization problem. Finally, in this paper ending, some illustrative examples are given in support of our results. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Memristive neural network Super-twisting algorithm Quantized control scheme Synchronization Time-varying delay

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Hierarchical Cooperative Swarm Policy Learning with Role Emergence

Hierarchical Cooperative Swarm Policy Learning with Role Eme...

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ieee symposium Series on computational intelligence (SSCI)

作者： Tianle Zhang Zhen Liu Zhiqiang Pu Tenghai Qiu Jianqiang Yi Chinese Academy of Sciences Institute of Automation Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728190495

Swarm systems can cooperatively and efficiently accomplish specified complex tasks. Recent works have shown the potential of multi-agent reinforcement learning methods to study behavior policies of swarm systems. However, it is difficult for them to complete complex swarm tasks efficiently. In human society, role assignment can effectively help humans understand complex tasks and decompose them into simple certain subtasks. Inspired by this, we propose a two-level hierarchical cooperative swarm policy learning framework with role emergence based on hierarchical deep reinforcement learning for distributed swarm systems. In this framework, roles are dynamic and emergent. Agents with the same role tend to collectively complete a certain subtask. Specifically, each agent uses a higher-level swarm policy to dynamically select a role for itself in a role space and at a higher temporal scale, while it uses a lower-level swarm policy to perform the responsibilities of the selected role in a primitive action space. Meanwhile, hierarchical swarm policies with partial observation are centrally trained and decentrally executed, where agents' local interaction modules and extrinsic team rewards are designed to promote cooperation among agents. In addition, an intrinsic reward is defined to enable different roles to be identified by agents' longer-term behaviors, which implicitly associates the roles with responsibilities. Simulation results show that our method can learn and generate emergent, dynamic and identifiable roles, which helps swarm systems to reliably and efficiently accomplish complex tasks in a shorter time.

关键词： Simulation Reinforcement learning Reliability Task analysis computational intelligence

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Energy-Efficient IoT Sensor Calibration With Deep Reinforcement Learning

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ieee ACCESS 2020年 8卷 97045-97055页

作者： Ashiquzzaman, Akm Lee, Hyunmin Um, Tai-Won Kim, Jinsul Chonnam Natl Univ Sch Elect & Comp Engn Gwangju 59626 South Korea Korea Elect Technol Inst Human IT Convergence Res Ctr Seoul 02792 South Korea Duksung Womens Univ Dept Cyber Secur Coll Sci & Technol Seoul 132714 South Korea

The modern development of ultra-durable and energy-efficient IoT based communication sensors has much application in modern telecommunication and networking sectors. Sensor calibration to reduce power usage is beneficial to minimizing energy consumption in sensors as well as improve the efficiency of devices. Reinforcement learning (RL) has been received much attention from researchers and now widely applied in many study fields to achieve intelligent automation. Though various types of sensors have been widely used in the field of IoT, rare researches were conducted in resource optimizing. In this novel research, a new style of power conservation has been explored with the help of RL to make a new generation of IoT devices with calibrated power sources to maximize resource utilization. A closed grid multiple power source based control for sensor resource utilization has been introduced. Our proposed model using Deep Q learning (DQN) enables IoT sensors to maximize its resource utilization. This research focuses solely on the energy-efficient sensor calibration and simulation results show promising performance of the proposed method.

关键词： Algorithm design and analysis optimization computational and artificial intelligence battery management systems simulation electronic design automation and methodology deeplearning reinforcement learning

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Bifurcations in a closed-loop model of tumor growth control

Bifurcations in a closed-loop model of tumor growth control

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International symposium on computational intelligence and Informatics

作者： Dániel András Drexler Ilona Nagy Valery Romanovski Physiological Controls Research Center Óbuda University Budapest Hungary Budapest University of Technology and Economics Institute of Mathematics Budapest Hungary Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia Center for Applied Mathematics and Theoretical Physics University of Maribor Maribor Slovenia Faculty of Natural Science and Mathematics University of Maribor Maribor Slovenia

ISBN: (纸本)9781665426855

Model-based therapy generation can open new horizons in medicine. Cancer chemotherapy can be optimized using control theoretic methods based on mathematical models of tumor growth. We carry out the qualitative analysis of such a model using the simplest control scheme, i.e., P type control. We look for bifurcations for realistic values of tumor parameters. We show that it is possible to have bifurcations in the closed-loop system, and the qualitative behaviour depends on the initial conditions, and it is independent of the control gain. The analysis shows that the system has rich dynamics and the model can be used to reproduce complex phenomena occurring during real therapies.

关键词： Drugs Analytical models Chemotherapy Simulation Limit-cycles Bifurcation Back

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Blockchain-based Consensus Study on Distributed control Systems

Blockchain-based Consensus Study on Distributed Control Syst...

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Digital Twins and Parallel intelligence (DTPI), ieee International Conference on

作者： Jing Zhu Hongchang Deng Xiang Li Yong Yuan Feiyue Wang College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Institute of Systems Engineering Macau University of Science and Technology Macau China School of Mathematics Renmin University of China Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

In this paper, two blockchain-based consensus mechanisms are proposed for distributed control systems, those are the proof-of-work-based (PoW-based) and proof-of-stake-based (PoS-based) consensus mechanisms. The basic idea and process of these blockchain-based consensus mechanisms are introduced, giving rise to the dynamic, impartial and efficient consensus compared with the consensus protocol achieved by traditional control theories.

关键词： Digital twin Conferences Decentralized control Process control control theory Consensus protocol computational efficiency

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Speeding-Up Complex RF IC Sizing Optimizations with a Process, Voltage and Temperature Corner Performance Estimator based on ANNs

Speeding-Up Complex RF IC Sizing Optimizations with a Proces...

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ieee International symposium on Circuits and Systems

作者： Pedro Vaz Antonio Gusmao Nuno Horta Nuno Lourenco Ricardo Martins Insiuo de Teecouniccoes PorugInsiuo de Teecouniccoes PorugInsiuo de Teecouniccoes PorugInsiuo de Teecouniccoes PorugInsiuo de Teecouniccoes Porug

ISBN: (数字)9781665484855

ISBN: (纸本)9781665484862

The automatic sizing of radio-frequency (RF) integrated circuit (IC) blocks in deep nanometer technologies has moved towards process, voltage, and temperature (PVT)-inclusive optimizations, to ensure their robustness. Each sizing solution is exhaustively simulated in a set of PVT corners, thus pushing modern workstations' capabilities to their limits. This paper presents innovative research towards the automation of RF IC design by using deep learning to assist the simulation-based sizing tools in time-consuming PVT-inclusive optimizations. The proposed PVT regressor inputs the circuit's sizing and the nominal performances to estimate the PVT corner performances via multiple parallel artificial neural networks. Two control phases prevent the optimization process from being misled by inaccurate performance estimates. The proposed controlled PVT estimator is tested on a state-of-the-art class C/D voltage-controlled oscillator, reducing the workload of the circuit simulator up to 79% while achieving a speed-up factor of 2.92 , ultimately saving more than 16 days of computational effort.

关键词： Integrated circuits Radio frequency Deep learning Temperature Voltage-controlled oscillators Process control Artificial neural networks

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A control Loop-based Algorithm for Operational Transformation 14

A Control Loop-based Algorithm for Operational Transformatio...

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ieee 14th International symposium on Applied computational intelligence and Informatics (SACI)

作者： Gadea, Cristian Ionescu, Bogdan Ionescu, Dan Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada

ISBN: (纸本)9781728173764

Operational Transformation (OT) has emerged as a viable theoretical principle for the implementation of real-time collaboration applications. In such systems, the collaboration consists of operations generated by members of a group who are performing concurrent actions on the same document or content. This powerful multi-user co-editing has been researched ever since the seminal works of the late 1980s. As the web evolved into a dominant platform for content consumption and creation, classes of algorithms like OT and Conflict-free Replicated Data Types (CRDT) have enabled flexible content synchronization for applications such as online word processors. Despite their long history in academia, OT and CRDT continue to have unsolved issues due to the centralized approach required for scalable and reliable web-based document editing. This paper proposes a control Loop-based OT approach based on a serverless architecture and on Finite State Automata (FSA). A control loop principle is used to design a series of algorithms for distributed conflict resolution. The proposed architecture consists of a series of blocks which internally contain a number of multi-level Finite State Machines. The architecture of the new serverless approach for OT is introduced and the basic FSAs that model the co-editing processes are described. Cases encountered in the dynamics of the co-editing processes were modeled to prove that the essential OT properties of causality preservation, convergence, and intention preservation are all satisfied. Simulation results are given at the end of the paper.

关键词： control Loop Architecture Decision Making Automata Collaborative Software Platforms Distributed Computing Systems Consistency and Concurrency Finite State Automata Real-Time Automata Real-Time Systems

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