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Asian control Conference

作者： Guicheng Wang Liang Yuan Zhicheng Bai Guoliang Cai Ning Hua Xiaobin Li School of Electrical and Electronics Engineering Shanghai Institute of Technology Shanghai China State Key Laboratory of Intelligent Optimized Manufacturing in Mining & Metallurgy Process and Beijing Key Laboratory of Process Automation in Mining & Metallurgy Beijing China Zijin Intelligent Control (Xiamen) Technology Co. Ltd. Xiamen China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

The engineering application under industrial big-data analysis is of great significance for improving the optimization effect of enterprise production process control processes. By analyzing the operating principle of the semi-automatic mill and studying its control optimization strategy, based on the operational data of the SAG mill, industrial big-data analysis is adopted to self-learning its control optimization rules. Firstly, SPSS is used to preprocess the high-dimensional process data generated during the operation of the semi-automatic mill. Four parameters, namely power, axial pressure, grinding sound, and grinding concentration, are preliminarily selected. Then, PCA is used to screen and reduce the dimensionality of multidimensional data, and K-Means clustering algorithm is used to classify and identify the reduced dataset. After simulation research, the results show that PCA can reduce the redundancy of SAG mill operation data, and the control optimization rules formed by self-learning can serve as operational guidance for improving the efficiency and energy-saving of SAG mill operation. The effectiveness can be further verified in practical engineering applications in the later stage.

关键词： Dimensionality reduction Energy consumption Technological innovation Redundancy Force process control Clustering algorithms

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Corrigendum to"Balance of Communication and Convergence: Predefined-time Distributed Optimization Based on Zero-Gradient-Sum"

arXiv

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arXiv 2024年

作者： Zhang, Renyongkang Guo, Ge Zhou, Zeng-Di College of Information Science and Engineering Northeastern University Shenyang110819 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao066004 China

This paper proposes a distributed optimization algorithm with a convergence time that can be assigned in advance according to task requirements. To this end, a sliding manifold is introduced to achieve the sum of local gradients approaching zero, based on which a distributed protocol is derived to reach a consensus minimizing the global cost. A novel approach for convergence analysis is derived in a unified settling time framework, resulting in an algorithm that can precisely converge to the optimal solution at the prescribed time. The method is interesting as it simply requires the primal states to be shared over the network, which implies less communication requirements. The result is extended to scenarios with time-varying objective function, by introducing local gradients prediction and non-smooth consensus terms. Numerical simulations are provided to corroborate the effectiveness of the proposed algorithms. © 2024, CC BY.

关键词： Consensus algorithm

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Passivity-Based Online Reinforcement Learning for Real Time Model-Free Overhead Crane System control

Passivity-Based Online Reinforcement Learning for Real Time ...

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第34届中国控制与决策会议

作者： Haoran Zhang Chunhui Zhao Jinliang Ding State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University

In this paper,a novel model-free online Reinforcement Learning(RL) control method is proposed for the real-time overhead crane control *** crane control problem is first formulated as an optimal regulation problem with a user-specified objective *** neural-networks,namely Actor-Critic networks,are employed to approximate the objective function and the optimal control policy ***,an improved network updating rule with an additional passivity-based stabilization term is developed to remove the requirement of the initial stabilizing control *** other crane control approaches,the proposed online RL algorithm does not rely on prior knowledge of the overhead crane mathematical ***,simulation studies are carried out to demonstrate the effectiveness of the proposed method in the presence of system parameter variations when compared to LQR control.

关键词： Overhead cranes Reinforcement Learning Q-learning Data-driven control

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Multimodal process Monitoring Based on Dynamic Extended K-means-VAE-RF

Multimodal Process Monitoring Based on Dynamic Extended K-me...

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Chinese control and Decision Conference, CCDC

作者： Shiwei Su Kaixiang Peng Xueyi Zhang University of Science and Technology Beijing Key Laboratory for Advanced Control of Iron and Steel Process of Ministry of Education School of Automation and Electrical EngineeringBeijingPeople's Republic of China100083

With the development of customization and flexibility of manufacturing industry, intelligent manufacturing process gradually presents multimodal characteristics, which are reflected in the strong coupling, nonlinear, multi working conditions and other characteristics of the process. In this paper, a multi-modal process monitoring method based on dynamic expansion is proposed. In view of the dynamic characteristics of process data, the process data is dynamically expanded through the amplification matrix, and then the multi-modal process data is modal divided through the improved K-means algorithm. The divided multi-modal process data is monitored using Variational Autoencoder, and relevant statistics and control limits are designed. Finally, the multi-modal process monitoring is constructed by introducing the method of random forest for modal identification. The validity of the algorithm is verified by real data of steel rolling process.

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Stealthy False Data Injection Attacks in Multi-Channel Vehicular Communication: White-Box and Gray-Box Strategies

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IEEE Transactions on Vehicular Technology 2025年

作者： Xu, Chongcong Zheng, Fangfang Guo, Ge Southwest Jiaotong University School of Transportation and Logistics Chengdu611756 China Southwest Jiaotong University National Engineering Laboratory of Integrated Transportation Big Data Application Technology National United Engineering Laboratory of Integrated and Intelligent Transportation Chengdu611756 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Northeastern University at Qinhuangdao School of Control Engineering Qinhuangdao066004 China

Understanding the vulnerabilities of vehicular networks from an attacker's perspective is crucial for identifying stealthy false data injection (FDI) attacks and developing robust defense methods. This paper investigates stealthy FDI attacks in multi-channel vehicular communication systems. We construct a multi-source state estimation system using a sequential Kalman filter to integrate and estimate redundant state information transmitted by preceding vehicles across multiple channels. To enhance the system's resilience against FDI attacks, we incorporate a Sage-Husa adaptive filter and a chi-squared detector, which dynamically estimate and detect channel noise based on estimation errors. Within this framework, we utilize real-time state information and channel transmission residual to determine the probability of an attack window occurring. The attack process is divided into three phases, during which critical noise disturbances are introduced to create attack windows, allowing the attack to progressively align with the target state. Based on this analysis, we develop an optimization model for attack generation with complete channel information (AG-with-CCI) to facilitate a white-box attack. Additionally, acknowledging that attackers may not have access to real-time information from all channels, we analyze the iterative equations of state estimation errors and residuals to establish the conditions under which stealthy FDI attacks can be successfully executed, enabling the attack generation with attacked channel information (AG-with-ACI) to achieve a gray-box attack. Numerical simulations demonstrate that both attack methods can evade current detection mechanisms and achieve their intended objectives. © 2025 IEEE.

关键词： Adaptive filtering

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Small Object Detection Algorithm Based on RPANet and Positional Convolution Attention Mechanism 5

Small Object Detection Algorithm Based on RPANet and Positio...

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5th International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2022

作者： Tang, Zongbing Yang, Dan Qu, Junsuo School of Communication and Information Engineering Xi'an University of Posts and Telecommunications China School of Automation Xi'an Key Laboratory of Advanced Control and Intelligent Process Xi'an Robertic Intelligent Systems International Science and Technology Cooperation Base Xi'an University of Posts and Telecommunications Shaanxi Xi'an China

ISBN: (纸本)9781450396899

With the development of deep learning, small object detection has a significant role in application fields such as smart factories and remote sensing images. In order to address the problem of difficult and low accuracy detection of small objects due to small pixel scale and little feature information. In this paper, we present a path aggregation network with residual characteristic RPANet on YOLOv3 algorithm, which can twice use the feature information of the backbone network to enhance the small object feature information, and also offer a positional convolution attention mechanism module PCAM to thoroughly learn and extract the small object feature information as well as reduce the unnecessary feature information in the background, so as to further enhance the detection capability of the model for small objects. The experimental results demonstrate that the improved YOLOv3 algorithm is more effective for small object detection. © 2022 ACM.

关键词： Convolution

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IF-Based Trajectory Planning and Cooperative control for Transportation System of Cable Suspended Payload With Multi UAVs

IF-Based Trajectory Planning and Cooperative Control for Tra...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yu Zhang Jie Xu Cheng Zhao Jiuxiang Dong the State Key Laboratory of Synthetical Automation for Process Industries and the Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education College of Information Science and Engineering Northeastern University Shenyang P.R. China

In this paper, we tackle the control and trajectory planning problems for the cooperative transportation system of cable-suspended payload with multi Unmanned Aerial Vehicles (UAVs). Firstly, a payload controller is presented considering the dynamic coupling between the UAV and the payload to accomplish the active suppression of payload swing and the complex payload trajectory tracking. Secondly, different from the simplification of obstacles in most approaches, we propose three Insetting Formation (IF) algorithms for the complete obstacle shape to generate collision-free waypoints for the cooperative transportation system. An IF strategy is proposed by integrating three IF algorithms to improve the success rate of obstacle avoidance and reduce the algorithm complexity for performing the aggressive flight. Finally, we verify the robustness and high performance of the proposed algorithm through benchmark comparison and real-world experiments. Moreover, our source code is released as an open-source ros package.

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Cooperative Optimal Output Tracking for Discrete-Time Multiagent Systems: Stabilizing Policy Iteration Frameworks and Analysis

arXiv

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arXiv 2025年

作者： Li, Dongdong Dong, Jiuxiang College of Information Science and Engineering Northeastern University Shenyang110819 China State Key Laboratory of Synthetical Automation of Process Industries Northeastern University Shenyang110819 China Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education Northeastern University Shenyang110819 China

In this paper, two model-free optimal output tracking frameworks based on policy iteration for discrete-time multiagent systems are proposed. First, we establish a framework of stabilizing policy iteration that can start from any initial feedback control policy, relaxing the dependence of traditional policy iteration on the initial stabilizing control policy. Then, another efficient and equivalent Q-learning policy iteration framework is developed, which is shown to require only less system data to get the same results as the stabilizing policy iteration. Both frameworks obtain stabilizing control policy by iterating the stabilizing virtual closed-loop system step-by-step to the actual closed-loop system. Multiple explicit schemes for the iteration step-size/coefficient are designed and their stability during the above iterations is analyzed. By using the generated closed-loop stabilizing control policy and two frameworks, the optimal feedback control gain is obtained. The approximate solution of the regulator equations is found by model-free iteration, which leads to the optimal feedforward gain. Finally, the cooperative optimal output tracking is realized by a distributed feedforward-feedback controller. The proposed algorithms are validated by simulation. Copyright © 2025, The Authors. All rights reserved.

关键词： Feedback control

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A Koopman Operator-Based Finite Impulse Response Filter for Nonlinear Systems

A Koopman Operator-Based Finite Impulse Response Filter for ...

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IEEE Conference on Decision and control

作者： Zhichao Pan Biao Huang Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China department of chemical and materials engineering University of Alberta Edmonton Alberta Canada

This paper proposes a novel Koopman operator-based finite impulse response (KFIR) filter for nonlinear dynamic systems. This filter is generalized from the minimum variance unbiased (MVU) FIR filter for linear systems by using a global linear approximation of the nonlinear dynamics obtained from Koopman operator theory and the extended dynamic mode decomposition (EDMD) algorithm. Based on the recursive linear model, a reduced-order FIR filtering structure is proposed, and the optimal gain is derived to minimize the trace of the estimation error covariance. Unlike traditional methods, the KFIR filter requires no prior knowledge of the initial state and fully utilizes the data of a moving horizon. Simulation results show that the proposed filter has excellent robustness against unexpected modeling uncertainties and inaccurate noise information, making it suitable for real applications.

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Study of Cracking Mechanism and Wear Resistance in Laser Cladding Coating of Ni-based Alloy

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Chinese Journal of Mechanical engineering 2021年第5期34卷 259-272页

作者： Zhenglei Yu Lunxiang Li Deqiang Zhang Guangfeng Shi Guang Yang Zezhou Xu Zhihui Zhang Key Lab of Bionic Engineering Ministry of EducationJilin UniversityChangchun 130022China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China College of Mechanical and Electric Engineering Changchun University of Science and TechnologyChangchun 130022China College of Mechanical Engineering and Automation Liaoning University of TechnologyJinzhou 121001China Key Laboratory of Fundamental Science for National Defense of Aeronautical Digital Manufacturing Process Shenyang Aerospace UniversityShenyang 110136China

Nickel-based alloy coatings were widely used for the remanufacturing of dies and moulds by laser cladding,but the crack sensitivity would be increase due to the higher strength and hardness,which reduced the wear resistance of Ni-based *** this paper,Ni-based coatings with the addition of a plastic phase(an austenitic stainless net)were prepared using laser cladding technology,and the CeO_(2)was added in cladding *** cracking mechanism,microhardness,microstructure,phase composition,and wear properties were *** relationship between thermal stress and the elastic and plastic fracture had been developed from the standpoint of fracture mechan-ics and thermal elastic fracture *** fracture criterion of the nickel-based coating was obtained,and the study has shown that the crack sensitivity could be reduced by decreasing the thermal expansion coefficientΔα.Thus,a new method was proposed,which the stainless steel nets were prefabricated on the *** was found that the number of cracks reduced significantly with the addition of stainless steel *** the stainless steel net with 14 mesh was added in Ni-based coatings,the average microhardness of nickel composite coating was 565 HV_(0.2),which was 2.6 times higher than that of the 45 steel *** the rare earth oxide 4 wt.%CeO_(2)and stainless steel net were added in the Ni-based coating reducing the microhardness(the average microhardness is 425 HV_(0.2)),the wear resistance of it improved *** wear volume of Ni-based composite coating was 0.56×10^(−5) mm^(3)·N^(−1)·m^(−1),which was 85.1%lower than that of 45 *** experiment results have shown that the Nickel-based composite coating is equipped with low crack sensitivity and high abrasive resistance with austenitic stainless net and the rare earth oxide 4 wt.%*** research offers an efficient solution to produce components with low crack susceptibility and high wear-resistance coatings fabricated

关键词： Laser cladding Wear resistance Crack sensitivity Stainless steel net Rare earth oxide

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