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Secure Synchronization control for a Class of Cyber-Physical Systems With Unknown Dynamics

IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1215-1224页

作者： Ning Wang Xiaojian Li College of Information Science and Engineering Northeastern UniversityShenyang 110819China State Key Laboratory of Synthetical Automation for Process Industries Northeastern Universityand with the Key Laboratory of Vibration and Control of Aero-Propulsion SystemMinistry of EducationNortheastern Universityand also with the College of Information Science and EngineeringNortheastern UniversityShenyang 110819China IEEE

This paper investigates the secure synchronization control problem for a class of cyber-physical systems(CPSs)with unknown system matrices and intermittent denial-of-service(DoS)*** the attack free case,an optimal control law consisting of a feedback control and a compensated feedforward control is proposed to achieve the synchronization,and the feedback control gain matrix is learned by iteratively solving an algebraic Riccati equation(ARE).For considering the attack cases,it is difficult to perform the stability analysis of the synchronization errors by using the existing Lyapunov function method due to the presence of unknown system *** order to overcome this difficulty,a matrix polynomial replacement method is given and it is shown that,the proposed optimal control law can still guarantee the asymptotical convergence of synchronization errors if two inequality conditions related with the DoS attacks ***,two examples are given to illustrate the effectiveness of the proposed approaches.

关键词： Algebraic Riccati equation(ARE) complex dynamical networks(CDNs) denial-of-service(DoS) secure control

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Finite-time Consensus for Third-Order Multi-Agent Systems with Directed Communication Networks

Finite-time Consensus for Third-Order Multi-Agent Systems wi...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Xirui Zhang Zhi-Liang Zhao Tengfei Liu Zhong-Ping Jiang School of Mathematics and Statistics Shaanxi Normal University Xi’an P. R. China School of Electrical and Control Engineering North University of China Taiyuan P. R. China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang P. R. China Department of Electrical and Computer Engineering New York University Brooklyn NY USA

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This paper focuses on third-order multi-agent systems with directed communication networks. It is for the first time that the finite-time consensus problem is solved for third-order multi-agent systems under digraphs containing spanning trees. Two explicit-coefficient finite-time protocols, namely, edge-based and node-based, are proposed. First, we prove that asymptotic consensus is achievable with the reduced linear protocol. Then, we show that finite-time consensus is achievable with our explicit-coefficient finite-time protocols through homogeneous theory. Finally, numerical simulations are carried out to demonstrate the effectiveness of the proposed protocols.

关键词： Protocols Network topology Numerical simulation Topology Communication networks Closed loop systems Multi-agent systems

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Enhanced Soft Sensor with Qualified Augmented Data Using Centroid Measurement Criterion

Enhanced Soft Sensor with Qualified Augmented Data Using Cen...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Yun Dai Qing Yu Tao Yang Yuan Yao Yi Liu Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China National Tsing Hua University Hsinchu Taiwan

ISBN: (纸本)9781665402460

Development of reliable soft sensors using limited labeled samples is not an easy task in industrial processes. A selective generative adversarial network (SGAN)-based support vector regression (SGAN-SVR) soft sensor is proposed for quality prediction using limited labeled training data. Specifically, SVR is considered as a base prediction model. The Wasserstein GAN (WGAN) is adopted to capture the distribution of available labeled data and generate virtual candidates. Subsequently, using a proposed similarity measurement strategy, those synthetic data with more information are selected and introduced into the training set. Using the designed data augmentation approach, the SGAN-SVR model can achieve better prediction performance compared with the SVR soft sensor. The quality prediction results on an industrial polyethylene process demonstrate the effectiveness and advantages of the proposed method.

关键词： Training Support vector machines Polyethylene Filtering Soft sensors Training data Predictive models

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Deep Graph Network for process Soft Sensor Development

Deep Graph Network for Process Soft Sensor Development

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Mingwei Jia Yun Dai Danya Xu Tao Yang Yuan Yao Yi Liu Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China National Tsing Hua University Hsinchu Taiwan

ISBN: (纸本)9781665402460

In the (bio)chemical processes, traditional hardware sensors are difficult to directly measure the quality of critical products due to their time-varying, non-linear, and dynamic characteristics. This makes process soft sensor modeling methods important. Since the process variables can be regarded as natural graph data, this work introduces graphs in the soft sensor modeling area. A soft sensor model based on the graph neural network (GNN) is proposed. The model can learn the topological structure of graph data between each unit variable. Moreover, it characterizes variable relationships from the spatial and temporal dimensions to the output prediction by introducing the spatial-temporal convolutional layer. The effectiveness and advantages of the GNN-based soft sensor model are verified using a simulated fermentation process.

关键词： Soft sensors Computational modeling Predictive models Sensor phenomena and characterization Data models Product design Hardware

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Simple Model and Predictive control of a Pharmaceutical Batch Fluidized Bed Dryer

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IFAC-PapersOnLine 2021年第3期54卷 7-12页

作者： Francis Gagnon André Desbiens Éric Poulin Jocelyn Bouchard Pierre-Philippe Lapointe-Garant Process Observation and Optimization Laboratory (LOOP) Université Laval Quebec City G1V 0A6 Canada Process Monitoring Automation and Control group (PMAC) Pfizer Canada ULC Montreal H9J 2M5 Canada

The fluidized bed theory can be complex, especially for heterogeneous flow descriptions with bypasses, generally resulting in large differential and algebraic systems of equations. Consequently, their applicability to model-based process control is limited. In this work, a simplified homogeneous model for pharmaceutical batch drying is derived from the two-phase fluidization theory using physical insights and simplifying assumptions, reducing more than a hundred equations to five. A nonlinear model predictive controller with an internal model structure is designed from these simple equations, showing the simplicity of tuning and implementation. Parameters of the model are calibrated through nonlinear grey-box identification using pilot scale experimental data. The validation demonstrates that the proposed simplifications do not impair the ability to replicate the process dynamics adequately with experimental conditions similar to the ones used for calibration. Closed-loop results in simulation attest the robustness of this control strategy.

关键词： Modeling Identification Model-based control Batch processes

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Optimal control of plate motion and camber in a reversing rolling mill ⁎

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IFAC-PapersOnLine 2020年第2期53卷 11962-11967页

作者： C. Pietschnig A. Ettl U. Knechtelsdorfer A. Steinboeck A. Kugi Christian Doppler Laboratory for Model-Based Process Control in the Steel Industry Automation and Control Institute (ACIN) TU Wien Vienna Austria Automation and Control Institute (ACIN) TU Wien Vienna Austria

In plate rolling, reversing roughing mills are commonly used as a first processing step after casting. They are typically equipped with edger rolls for width reduction. During a rolling pass, lateral asymmetries like temperature gradients or thickness inhomogeneities can cause two major problems. The plate may rotate in the rolling gap and thus move in lateral direction. Another problem is that the plate may leave the mill stand with a cambered shape. In the worst case, these problems entail collisions with the mill stand or other equipment along the roller table. It is an essential control task to avoid such problems. In general, the exit thickness profile and the motion of the plate are controlled by adjusting the roll gap height. The latter has also an influence on the contour shape but, for active control of the plate width and contour shape, the use of edger rolls is more common. This is especially true if the roll gap adjustment is self-retaining, meaning that it cannot be adjusted during a rolling pass. In this work, such a roughing mill and its edger rolls are considered. A mathematical model for the motion and the camber of the plate is derived. Based on this model, a linear quadratic regulator (LQR) for both the plate motion and the resulting camber is developed. It uses the lateral forces of the edgers as control inputs. In a cascaded control structure, these forces are regulated by a subordinate admittance controller. The developed control system is validated in simulation studies.

关键词： Heavy-plate hot rolling roughing mill with edger rolls steel industry model-based control camber control optimal control Riccati equation

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Input-output finite-time sliding mode fault-tolerant control for Markovian jump systems with incomplete transition rates

Input-output finite-time sliding mode fault-tolerant control...

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Chinese control and Decision Conference, CCDC

作者： Meng Zhao Haijuan Zhao Zhiru Cao Yugang Niu Ministry of Education The Key Laboratory of Smart Manufacturing in Energy Chemical Process (East China University of Science and Technology) Shanghai China School of Information and Control Engineering Qingdao University of Technology Qingdao China School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9781665478977

This paper deals with the input-output finite-time sliding mode control (SMC) problem of a class of uncertain Markovian jump systems with incomplete transition rates. It is assumed that the actuator failure may occur. A mode-dependent sliding surface is constructed. By synthesizing a fault-tolerant SMC scheme, the specified sliding surface can be reached in finite time. Furthermore, the input-output finite-time stability over both the reaching and sliding motion stages is ensured simultaneously by establishing some sufficient conditions. Finally, the developed fault-tolerant SMC approach is verified by a numerical example.

关键词： Fault tolerance Actuators Sufficient conditions Fault tolerant systems Resists Sliding mode control Numerical stability

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Operating Performance Assessment of Complex Industrial process Based on Kernel Locally Linear Embedding PLS

Operating Performance Assessment of Complex Industrial Proce...

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第32届中国过程控制会议(CPCC2021)

作者： Chu Fei Mo Shuangshuang Wang Fuli Lu Ningyun Ma Xiaoping Research Center of Underground Space Intelligent Control Engineering of the Ministry of Education China University of Mining and Technology School of Information and Control Engineering China University of Mining and Technology State Key Laboratory of Automatic Control Technology for Mining and Metallurgy Process Beijing General Research Institute of Mining & Metallurgy State Key Laboratory of Integrated Automation for Process Industries Northeastern University College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Due to the process disturbances and uncertainties,the operating performance of industrial process may deviate from the optimal operating point along with ***,non-optimal operation may lead to decline production quality and economic *** it is significant to implement online assessment strategy and further analyze the actual process operating performance,so as to make the production process in the best operating performance as far as *** process data is strongly nonlinear due to the change of system state caused by the change of machine performance or operation *** this time,the relationship between the local nearest neighbor samples is ***,the existing methods of operating performance assessment for solving nonlinear problems only focus on the global structure of data,i.e.,the variance,while ignoring the local neighborhood structure in each performance ***,a new method called kernel locally linear embedding PLS(KLLEPLS) is developed and applied for operating performance *** includes offline modeling,online evaluation and non-optimal cause *** algorithm not only has concise expression and similar analytical solutions for PLS,but also retains the original geometric structure of strongly nonlinear data when extracting the maximum correlation information between process ***,the practice and effectiveness of the proposed method are demonstrated by the dense medium coal preparation process and Tennessee Eastman(TE) process.

关键词： Complex industrial process operating performance assessment kernel locally linear embedding PLS non-optimal cause identification

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Multivariate Time Delay Estimation Based on Dynamic Characteristic Analytics

Multivariate Time Delay Estimation Based on Dynamic Characte...

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第三十九届中国控制会议

作者： Xu Chen Chunhui Zhao State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University State Key Laboratory of Process Automation in Mining & Metallurgy Beijing Key Laboratory of Process Automation in Mining &Metallurgy

Time delay widely exists among industrial process variables, which may lead to invalid description of systems and reduce the model accuracy for soft sensor, process monitoring etc. Therefore, it is crucial to estimate time delay for improving model accuracy. In traditional research, time delay estimation（TDE） algorithm for two variables is fully investigated, but little research pays attention to multivariate. The method of pairwise comparison may not only cause high calculation complexity but also cut off the correlation between multivariate. In this work, a new TDE algorithm is proposed to estimate time delay between multivariate, which extracts dynamic latent variable to represent the process using improved dynamic inner PCA algorithm（DiPCA）. Dynamic latent variable extracts the autocorrelation and cross-correlation between process variables. Take it as a standard and analyze the time delay, so that the influence of multivariate variables could be comprehensively considered. Since there may be non-linear variables, the significant factor（SF） is used for variable selection, and the multivariate variables are divided into multiple linear subgroups, which makes the analysis result more reasonable. The effectiveness is illustrated with two numerical examples and the Tennessee Eastman process.

关键词： Time delay estimation process dynamics dynamic latent variable variable selection multivariate

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Distributed Event-Triggered Bandit Convex Optimization with Time-Varying Constraints

arXiv

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arXiv 2024年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China The Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Mathematics Southeast University Nanjing210096 China The Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms require that each agent broadcasts its decision to its neighbors at each iteration. To better utilize the limited communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. Copyright © 2024, The Authors. All rights reserved.

关键词： Convex optimization

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