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Safety stabilization of switched systems with unstable subsystems

control Theory and Technology 2022年第1期20卷 95-102页

作者： Lijun Long Yiguang Hong State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang110819LiaoningChina College of Information Science and Engineering Northeastern UniversityShenyang110819LiaoningChina Department of Control Science and Engineering Tongji UniversityShanghai201804China

This paper is concerned with the problem of safety stabilization for switched systems where the solvability of the problem under study for individual subsystems is not assumed.A new state-dependent switching strategy with guaranteed dwell-time for switched systems is constructed,and a sufficient condition for absence of Zeno behavior is ***,a novel switched control design method is proposed to simultaneously guarantee the safety of the switched closed-loop system and stabilize the system based on the union of a common barrier function and a single Lyapunov function,which effectively handles the conflict between safety and stability ***,two examples are presented to demonstrate the effectiveness of the proposed design approach.

关键词： Safety stabilization Switched systems Common barrier function Single Lyapunov function State-dependent switching

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A Sparse Quadratic Programming Approach to Supervisory control of Multi-Zone HVAC Systems with Consideration of Peak Demand Shaving and Thermal Comfort

A Sparse Quadratic Programming Approach to Supervisory Contr...

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International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： Pasitnat Sasananand David Banjerdpongchai Department of Electrical Engineering Faculty of Engineering Center of Excellence in Intelligent Control Automation for Process Systems Chulalongkorn University Bangkok Thailand

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

The HVAC system is one of the major power consuming equipment in buildings. Considering the effective setpoint temperature of each zone can increase efficiency in managing power usage in buildings, leading to the operating cost reduction. This paper presents the design of supervisory control (SC) for multi-zone HVAC systems that aims to minimize the total operating cost (TOC) and the thermal comfort cost (TCC). To minimize the TOC and TCC, both objectives are normalized and combined as a quadratic programming (QP) problem which can be efficiently solved. To achieve the design objective, two methods of SC are developed for multi-zone, namely, centralized SC and decentralized SC. We apply standard QP and sparse QP solvers using interior point method. The numerical results reveal that centralized SC performs better according to a tradeoff curve which TOC and TCC are lower. While both solvers give the same results, sparse solver can provide the solutions faster than interior point method. This paper demonstrates that centralized control is appropriate for implementation in multi-zones buildings and the sparse solver proves to be more suitable in the context of sparse QP problem.

关键词： HVAC Costs Buildings Supervisory control Telecommunications Quadratic programming Sparse matrices

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Single-channel ultrahigh frequency moisture meter with direct measurement of moisture content of bulk materials

Single-channel ultrahigh frequency moisture meter with direc...

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Automatics and Informatics (ICAI), International Conference

作者： Palvan I. Kalandarov Shakhnoza R. Ubaydullayeva Mirhalil A. Ismailov Nikola N. Nikolov Mariela Alexandrova Department "Automation and Control of Technology Process in Production" «Tashkent Institute of Irrigation and Agricultural Mechanization Engineers» National Research University Tashkent Uzbekistan Department of Automation Faculty of Computer Science and Automation Technical University of Varna Varna Bulgaria

ISBN: (数字)9798350353907

ISBN: (纸本)9798350353914

The article discusses the theoretical foundations of the design of a single-channel ultrahigh frequency moisture meter with direct measurement of the moisture content of bulk materials. In accordance with the requirements of the methodology for selecting efficiency criteria, it is necessary to develop structural diagrams of measuring devices. For these purposes, the standard deviation of the random error is determined, characterizing the accuracy. It includes the main components: sensitivity error, zero error and additive component. Mathematical models of structures are constructed and the standard deviation of random errors, which are caused by certain parameters and additive fluctuations, is calculated. A single-parameter ultrahigh-frequency method for determining the moisture content is proposed. This method provides high accuracy of a single-channel ultrahigh frequency moisture meter with direct measurement of the moisture content of bulk materials. The measuring device can be used in the agricultural industry, where humidity is one of the important parameters, starting with harvesting and ending with the release of finished products.

关键词： Meters Additives Accuracy Sensitivity Moisture UHF measurements Mathematical models Frequency measurement Informatics Standards

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The Specifics of the Organization of Independent Work of Students in the System of Secondary Vocational Education In Uzbekistan in the Context of the Transition to a Digital Economy 3

The Specifics of the Organization of Independent Work of Stu...

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3rd International Conference on Technology Enhanced Learning in Higher Education, TELE 2023

作者： Ubaydullayeva, Shakhnoza Tadjiyeva, Gavhar Ubaydullayeva, Dilorom Kadirova, Nilufar Gulyamova, Zarina Subanova, Dilafruz National Research University «tashkent Institute of Irrigation and Agricultural Mechanization Engineers» Department 'Automation and Control of Technology Process in Production' Tashkent Uzbekistan University Named after Nizami Department of Theory and Methodology of Teaching English Language Tashkent State Pedagogical Tashkent Uzbekistan

ISBN: (纸本)9798350326567

The problem of self-education of students of professional colleges is one of the most important in Uzbekistan. With the improvement of the education system, the processes of education and upbringing, new aspects of this problem appear, associated with changing the content and setting new tasks. Social transformations caused by the transition to the information society actualize the problem of the formation of a new paradigm of education, which is characterized by a redistribution of emphasis from educational activities to self-educational ones. The use of electronic educational resources (computer educational and methodological complexes, textbooks, teaching aids, virtual laboratories, stands, posters, etc.) is today one of the conditions for increasing the effectiveness of training - the psychological, theoretical and practical readiness of students of professional colleges for independent work. Uzbekistan's transition to a market economy dictates new requirements for a specialist, one of the main qualities of which is independence. The formation of this quality is determined, among other things, by the organization of independent work as a type of educational activity in educational institutions of secondary vocational education, which have their own specifics and features © 2023 IEEE.

关键词： Students

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A Semisupervised Soft-Sensor of Just-in-Time Learning With Structure Entropy Clustering and Applications for Industrial processes Monitoring

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 722-733页

作者： Li, Dong Liu, Yiqi Huang, Daoping Xu, Chong South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science and Engineering Guangzhou510640 China Technical University of Denmark Process and Systems Engineering Center Department of Chemical and Biochemical Engineering Lyngby2800 Denmark South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Gannan Normal University School of Physics and Electronic Information Ganzhou341000 China

To monitor industrial processes properly, soft-sensors are widely used to predict significant but difficult-to-measure quality variables. However, the prediction performances of traditional data-driven soft-sensors are usually unacceptable once suffering from high-nonlinear, high-dimension, and imblance data issues. Therefore, a semisupervised soft-sensor, which is learned by a just-in-time method with structure entropy clustering (SS-JITL-SEC), is proposed aiming to improve prediction performance with a simpler way. Inspired by a divide and conquer strategy, a novel SEC method is proposed to achieve several clusters and then to translate the highly complex and nonlinear modeling problems into simple and linear ones. Moreover, the training dataset is extended through a mixed SS labeling approach. Finally, dissimilarity-based JITL works together with the resulting clustering subdatasets to formulate a local adaptive prediction model. Two datasets from different types of wastewater treatment plants are used to verify the effectiveness of the proposed soft-sensor. The results show that the SS-JITL-SEC soft-sensor can achieve better prediction performance than other standard counterparts, and even for effective process monitoring with the resulted residuals. © 2020 IEEE.

关键词： Entropy

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Extended NNs-Based Adaptive Event-Triggered Asymptotic control for Nonlinear Systems Against Actuator Faults 7

Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

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7th International Symposium on Autonomous Systems, ISAS 2024

作者： Liu, Shanlin Zhang, Yingwei Zhao, Xudong Wang, Hesheng Northeastern University College of Information Science and Engineering Shenyang China Northeastern University State Laboratory of Synthesis Automation of Process Industry Shenyang China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350363173

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent. © 2024 IEEE.

关键词： Approximation algorithms

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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 812-833页

作者： Xinlei Yi Shengjun Zhang Tao Yang Tianyou Chai Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technologyand also affiliated with the Digital FuturesStockholm 10044Sweden Department of Electrical Engineering University of North TexasDentonTX 76203 USA IEEE State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is *** problem is an important component of many machine learning techniques with data parallelism,such as deep learning and federated *** propose a distributed primal-dual stochastic gradient descent(SGD)algorithm,suitable for arbitrarily connected communication networks and any smooth(possibly nonconvex)cost *** show that the proposed algorithm achieves the linear speedup convergence rate O(1/(√nT))for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak-Lojasiewicz(P-L)condition,where T is the total number of *** also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global *** demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms.

关键词： Distributed nonconvex optimization linear speedup Polyak-Lojasiewicz(P-L)condition primal-dual algorithm stochastic gradient descent

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Simulation Analysis and Model Modification of the LWR Traffic Flow Theory

Simulation Analysis and Model Modification of the LWR Traffi...

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IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO

作者： Yang Chen Jun Fu Anton Selivanov State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Department of Automatic Control and Systems Engineering University of Sheffield UK

ISBN: (数字)9798350344639

ISBN: (纸本)9798350344646

The surge in urbanization and ensuing traffic congestion underscores the imperative for contemporary traffic flow control models. This paper explores the Lighthill-Whitham-Richards (LWR) theory in the macroscopic domain of traffic flow control. It evaluates the accuracy and mathematical logic of simulation performance of related models, namely Greenshields, Newell-Daganzo, Greenberg, Underwood, and California. This paper employs thorough simulations that utilize a holistic three-dimensional(3D) analysis based on time, location, and density. It provides a comprehensive comparison and discusses specific features of each model. Additionally, a modification to the macroscopic model is proposed. The modified model overcomes the shortcomings of performing well only in some specific short ranges and achieves a full range of application effects. The study offers valuable guidance for real-life scenario selections and applications in the traffic domain.

关键词： Analytical models Accuracy Urban areas Transportation Predictive models Mathematical models Numerical models

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Time-Attention Graph Convolutional Network Soft Sensor in Biochemical processes 4

Time-Attention Graph Convolutional Network Soft Sensor in Bi...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Jia, Mingwei Xu, Danya Yang, Tao Yao, Yuan Liu, Yi Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering 30013 Taiwan

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

Most data-driven soft sensor methods can model nonlinear time-varying characteristics of biochemical processes. However, the intrinsic relationship between variables, which is helpful for understanding model behavior, has rarely been investigated in existing data-driven methods. In this work, a novel soft sensor model of time-attention graph convolutional network (TA-GCN) is proposed, which jointly leverages variable relationships and long-term temporal dependencies to improve interpretability and prediction accuracy. This model first uses the maximum information coefficient to construct a topology graph and trains edge strengths end-to-end. The data are then encoded in the spatial-temporal dimension based on GCN and attention mechanism. Finally, the empirical knowledge that analyzes the operating state of the process and graph are combined to explain the model behavior. In comparison to existing soft sensors, TA-GCN enables efficient and scalable training for long-term spatial-temporal dependencies. Experimental results on InPenSim dataset demonstrate that TA-GCN is competitive with state-of-the-art methods. © 2022 IEEE.

关键词： Convolution

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Topology-Informed Graph Convolutional Network for Fault Diagnosis 11

Topology-Informed Graph Convolutional Network for Fault Diag...

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11th IEEE Data Driven control and Learning Systems Conference, DDCLS 2022

作者： Jia, Mingwei Liu, Yi Xu, Danya Yang, Tao Yao, Yuan Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering 30013 Taiwan

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

The development of an accurate data-driven fault diagnosis model faces several obstacles. One significant challenge is how to combine the model with the process mechanism rationally and improve the model interpretability. In this work, a fault diagnosis method based on a topology-informed graph convolutional network (TIGCN) is proposed. This model first uses the empirical knowledge that analyzes the operating state of the process and combines the operating data to construct a signed directed graph. Then the operating data is divided into three modalities in the time dimension. The model utilizes a well-designed spatial-temporal convolutional layer and signed directed graph to construct different modalities separately to effectively detect fault types. The superior fault diagnosis performance of the proposed TIGCN model is demonstrated on the Tennessee-Eastman process as compared to traditional approaches. © 2022 IEEE.

关键词： Failure analysis

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