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2023 IEEE Conference on control Technology and Applications, CCTA 2023

作者： Birs, Isabela R. Muresan, Cristina I. Susca, Mircea Mihaly, Vlad Mihai Ghita, Mihaela Ghita, Maria De Keyser, Robin Ionescu, Clara Eedt Decision & Control Flanders Make Consortium Tech Lane Science Park 125 and 131 GhentB-9052 Belgium Ghent University Research Group of Dynamical Systems and Control Faculty of Engineering and Architecture Belgium Technical University of Cluj Napoca Department of Automation Memorandumului nr 28 Cluj-Napoca400114 Romania

ISBN: (纸本)9798350335446

This paper presents an original theoretical and implementation framework of fractional order event-based control with the purpose of quality improvement at the end production line of a continuous casting process. A real-life steel manufacturing plant is taken into consideration in the study. A prior fractional order model is considered to tune a fractional order Proportional Integral controller that ensures an ideal flow velocity of liquid steel. A novel event-based fractional order methodology is proposed that uses internal and external process events in order to improve quality. The implementation strategy takes into consideration available software and hardware components at the plant site, offering a realistic and implementable solution, highly suitable for the current steel industry setting. Numeric simulations successfully validate the proposed methodology. © 2023 IEEE.

关键词： Steelmaking

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Distributed Optimization with Gradient Descent and Quantized Communication

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IFAC-PapersOnLine 2023年第2期56卷 5900-5906页

作者： Apostolos I. Rikos Wei Jiang Themistoklis Charalambous Karl H. Johansson Division of Decision and Control Systems KTH Royal Institute of Technology SE-100 44 Stockholm Sweden Digital Futures SE-100 44 Stockholm Sweden Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia Cyprus

In this paper, we consider the unconstrained distributed optimization problem, in which the exchange of information in the network is captured by a directed graph topology, thus, nodes can only communicate with their neighbors. Additionally, in our problem, the communication channels among the nodes have limited bandwidth. In order to alleviate this limitation, quantized messages should be exchanged among the nodes. For solving this distributed optimization problem, we combine a gradient descent method with a distributed quantized consensus algorithm (which requires the nodes to exchange quantized messages and converges in a finite number of steps). Specifically, at every optimization step, each node (i) performs a gradient descent step (i.e., subtracts the scaled gradient from its current estimate), and (ii) performs a finite-time calculation of the quantized average of every node's estimate in the network. As a consequence, this algorithm approximately mimics the centralized gradient descent algorithm. We show that our algorithm asymptotically converges to a neighborhood of the optimal solution with linear convergence rate. The performance of the proposed algorithm is demonstrated via simple illustrative examples.

关键词： Distributed optimization quantized communication directed graphs finite-time consensus

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End-to-end Automatic Targetless Calibration between Low-resolution LiDARs and Cameras based on Cross-modal Attention

End-to-end Automatic Targetless Calibration between Low-reso...

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Chinese control and Decision Conference, CCDC

作者： Tianyang Huang Jun-Guo Lu Ming Wei Qing-Hao Zhang Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

LiDARs and cameras, commonly used sensors on autonomous vehicles and robots, require precise calibration for accurate joint environmental perception. Current calibration methods, capable of adjusting both intrinsic and extrinsic parameters, often depend on physical targets or human intervention, making them unsuitable for automatic online calibration. Moreover, these methods are primarily optimized for dense point clouds, as they are often tuned on open datasets featuring high-quality point cloud data. However, low-resolution LiDARs, preferred for their cost-effectiveness, are prevalent in practical applications. To automate the calibration process while maintaining high precision on sparse point clouds, multi-modal image registration techniques are leveraged to develop an end-to-end, cross-attention-based neural network for automatic calibration of low-resolution LiDARs and Cameras. Specifically, given an initial perturbation on point clouds, our network is capable of recovering the true extrinsic parameters without manual intervention. Additionally, specialized input preprocessing and training strategies are incorporated to enhance performance with sparse point clouds. Promising results are achieved on both open datasets and custom sensor acquisitions, highlighting the effectiveness and adaptability of our network to diverse scenarios.

关键词： Point cloud compression Training Image registration Visualization Laser radar Perturbation methods Neural networks

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Short-Term Traffic Flow Prediction of Highway Tunnels Based on SSA and Improved TSK Fuzzy System

Short-Term Traffic Flow Prediction of Highway Tunnels Based ...

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Chinese automation Congress (CAC)

作者： Zhijing Huang Kang Chen Zhezhuang Xu Qinbo Zeng Zhibin Xu Education Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing College of Electrical Engineering and Automation Fuzhou University Fuzhou China

Aiming at the problem that the traffic flow has an low prediction accuracy due to varying randomness and high nonlinearity, an improved TSK fuzzy neural network prediction model by singular spectrum analysis is ***, the original traffic flow time series can be decomposed into several subseries by singular spectrum analysis (SSA). Then, the Takagi-Sugeno-Kang (TSK) fuzzy system was trained using simulated annealing genetic algorithm (SAGA) and minibatch gradient descent method (MBGD) combined with three techniques (RDA) of regularization, DropRule and *** prediction model of TSK fuzzy neural network is established to predict each subseries independently, and the forecasted traffic flow is obtained by superimposing the prediction results of each subseries. Finally, the traffic flow dataset of expressway tunnels in a city is used to verify the effectiveness of the model. Experimental results can show high traffic flow prediction accuracy of the model, and the model can accurately predict multiple different highway tunnels.

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A Causal Model-based Planner for the Reconfiguration of Continuous Processes

A Causal Model-based Planner for the Reconfiguration of Cont...

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2021 European control Conference, ECC 2021

作者： Reinartz, Christopher Thuesen Enevoldsen, Thomas Galeazzi, Roberto Ravn, Ole Technical University of Denmark Automation and Control Group Department of Electrical Engineering LyngbyDK-2800 Kgs Denmark

ISBN: (纸本)9789463842365

This paper presents a planning framework for discrete planning of human operations in highly automated industrial plants, where manual and automatic control coexist. Based solely on qualitative knowledge of the controlled continuous process represented through signed directed graphs, the planner exploits a greedy algorithm to determine the optimal action for the human operator upon changes in the process' operating conditions or reconfiguration of the control system due to faulty conditions. The planner results in a decision support tool that instructs the human operator on the best course of action. The planning framework and the resulting planner are demonstrated on a quadruple-tank system. © 2021 EUCA.

关键词： Directed graphs

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Formal control Synthesis via Safe Reinforcement Learning Under Real-Time Specifications

Formal Control Synthesis via Safe Reinforcement Learning Und...

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International Conference on control and automation (ICCA)

作者： Peng Lv Guangqing Luo Zhou He Xianwei Li Xiang Yin Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China School of Electrical and Control Engineering Shaanxi University of Science and Technology Xi'an China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

In recent years, reinforcement learning techniques have gained widespread application in control synthesis. However, in the context of safety-critical systems, employing trial-and-error based reinforcement learning may be unacceptable due to the potential risks it poses during the learning process. Consequently, the development of safe reinforcement learning techniques has become imperative. This paper addresses the challenge of safe reinforcement learning for controller synthesis, particularly when safety specifications are intricately linked to the real-time behavior of the system. To articulate time-sensitive requirements, we leverage Metric Interval Temporal Logic (MITL). To ensure safety throughout the learning process, we introduce an additional reactive controller called a shield. Specifically, the shield functions to reject any behavior that violates the real-time specifications, thus mitigating potential risks. The efficacy of our proposed approach is demonstrated through simulation results, highlighting its ability to satisfy safety constraints in the dynamic environment of controller synthesis.

关键词： Measurement Heuristic algorithms Simulation Process control Reinforcement learning Real-time systems Safety

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Asynchronous distributed charging protocol for plug-in electric vehicles

Journal of Economy and Technology

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Journal of Economy and Technology 2023年 1卷 29-47页

作者： Yunfan Zhang Yifan Su Yue Chen Feng Liu State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing China China Electric Power Planning & Engineering Institue Beijing China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Special Administrative Region China

The proliferation of plug-in electric vehicles (PEVs) advocates a distributed paradigm for coordinating PEV charging. Unlike existing primal-dual decomposition or consensus methods, this paper proposes a cutting-plane-based distributed algorithm considering a peer-to-peer (P2P) communication network, which enables asynchronous coordination among PEVs. First, an equivalent surrogate model is established by exploiting the duality of the original optimization problem, which masks the private information of individual users by equivalent transformation. Then, a cutting-plane based algorithm is derived to solve the surrogate problem in a distributed manner with intrinsic superiority to cope with various asynchrony. Critical implementation issues, including distributed initialization, distributed cutting-plane generation, and localized stopping criteria, are discussed in detail. Numerical tests on IEEE 37- and 123-node feeders with actual data illustrate that the proposed method is resilient to several asynchronies and admits the plug-and-play operation mode. The proposed methodology is expected to provide an alternative path toward the robust protocol for PEV charging.

关键词： Asynchronous algorithm Charging protocol Distributed optimization Plug-in electrical vehicles

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Analyzing Behavior Data of Students in the Classroom with Association Rule Mining

Analyzing Behavior Data of Students in the Classroom with As...

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Chinese automation Congress (CAC)

作者： Qingbo Zeng Zhezhuang Xu Song Zheng Chi Liu Qinqin Chai Ying Zhang Education Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing College of Electrical Engineering and Automation Fuzhou University Fuzhou China

Students behavior in the classroom has a close relation with the academic performance of students. With the widespread use of mobile phones, the students are easily distracted by mobile phones during the class. Therefore, analyzing the students behavior in the classroom becomes important to improve the quality of teaching. However, the existing methods for analyzing students behavior in the classroom, such as facial recognition, has low efficiency with large amounts of irrelevant data. And it also raises concerns about privacy and ethical issues. To solve this problem, in this paper, a novel mobile software called EasyClass has been developed to collect and quantify students behaviors. Based on the data collected by EasyClass, we propose to utilize user profiling to study students behavior in the classroom. The clustering algorithm is firstly employed to classify the data and generate semantically tags which describe students behavior in the classroom. Then a sequence and association rule analysis method is used to analyze the behavior tags and generated association rules. The results enable educators and non-expert users to gain a deeper understanding of students behavior in the classroom, and further improve the quality of the classroom teaching.

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Evolutionary Dynamics of Cooperation on Coupled Networks

Evolutionary Dynamics of Cooperation on Coupled Networks

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control Theory and Applications (ICoCTA), International Conference on

作者： Zhenyu Shi Qi Su Department of Automation Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331506155

ISBN: (纸本)9798331506162

Network reciprocity has been recognized as a crucial mechanism for promoting the evolution of cooperation. However, prior studies on network reciprocity have predominantly focused on isolated networks, neglecting the interconnected nature of real-world systems. In reality, many large-scale systems are closely coupled, where the interaction patterns between systems differ significantly from those within individual networks. Motivated by this observation, we construct a strategy evolution model on coupled networks to explore the effects of such interconnections. Our findings reveal that coupled networks foster cooperation more effectively than isolated networks. This advantage persists across various network structures, suggesting the universality of this phenomenon. Interestingly, we discover that the strength of the coupling plays a pivotal role: weaker coupling between networks is more conducive to the emergence and stability of cooperation compared to stronger coupling. These results high-light the importance of considering cross-system interactions in understanding and designing mechanisms to enhance cooperative behavior.

关键词： Couplings Stability analysis Large-scale systems control theory Game theory

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Cluster Consensus Problem on Time-varying Higher-Order Interaction Networks

Cluster Consensus Problem on Time-varying Higher-Order Inter...

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IEEE Conference on Decision and control

作者： Haoyu Wei Lulu Pan Haibin Shao Dewei Li Wenbin Yu Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper examines the cluster consensus problem of higher-order interaction networks on switching networks. The matrix-valued inter-agent coupling mechanism is employed to capture the higher-order interactions amongst neighboring agents. Specifically, for a higher-order interaction network with both positive definite and positive semi-definite coupling matrices, we examine the scenario in which the nullspace of positive semi-definite coupling matrices is constructed by a set of orthogonal basis vectors. From the perspective of the lower-order component graph -the projection of network structure onto the direction of each orthogonal basis–results on the explicit characterization of cluster consensus of higher-order interaction networks are provided. Moreover, for time-varying higher-order interaction networks, necessary and sufficient conditions are provided to ensure that a time-varying network shares the same steady-state values as the integral time-invariant network. Simulation results are provided to demonstrate the theory.

关键词： Couplings Sufficient conditions Network topology Simulation Switches Vectors Topology Steady-state Matrix decomposition Convergence

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