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New Results in Stabilization of Uncertain Nonholonomic Systems:An Event-Triggered Control Approach

Journal of Systems Science & Complexity 2021年第5期34卷 1953-1972页

作者： LIU Tengfei ZHANG Pengpeng WANG Mengxi JIANG Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110004China. Department of Electrical and Computer Engineering New York University370 Jay StreetBrooklynNY 11201USA

This paper reports latest developments in event-triggered and self-triggered control of uncertain nonholonomic systems in the perturbed chained *** order to tackle the effects of drift uncertain nonlinearities,nonholonomic constraints and nonsmooth aperiodic sampling in eventbased control,a novel systematic design scheme is proposed by integrating set-valued maps with stateseparation and state-scaling *** stability analysis of the closed-loop event-triggered control system is based on the cyclic-small-gain techniques that overcome the limitation of Lyapunov theory in the construction of Lyapunov functions for nonsmooth dynamical systems and enjoy inherent robustness properties due to the use of gain-based characterization of robust *** specifically,the closed-loop event-triggered control system is transformed into an interconnection of multiple input-tostate stable systems,to which the cyclic-small-gain theorem is applied for robust stability *** self-triggered mechanisms are also developed as natural extensions of the event-triggered control *** proposed event-based control design approach is new and original even when the system model is reduced to the ideal unperturbed chained ***,the proposed methodology is also applicable to a broader class of nonholonomic systems subject to state and input-dependent *** efficacy of the obtained event-triggered controllers is validated by a benchmark example of mobile robots subject to parametric uncertainties and a measurement noise such as bias in the orientation.

关键词： Event-triggered control nonholonomic systems self-triggered control stabilization

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Cross-organizational Full-chain Intelligent Collaborative Service Method in Cloud Manufacturing

Cross-organizational Full-chain Intelligent Collaborative Se...

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International Symposium on Autonomous Systems (ISAS)

作者： Feng Xue Hongrui Gao Yingwei Zhang College of Information Science and Engineering Northeastern University Shenyang China State Laboratory of Synthesis Automation of Process Industry Northeastern University Shenyang China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

For the problem of difficulty in cross-organizational full-chain large-scale collaborative service in cloud manufacturing, in order to enable a quality subject to have the capability of full connection and full linkage, intelligent optimized decision-making and agile business support, a method for considering the components of collaborative service elements at different levels and scales is proposed, and a collaborative service model including positive attributes and negative attributes is established. For solving of cross-organizational large-scale collaborative service being an NP-hard problem, this paper proposes a multi-block two-stage genetic algorithm that reasonably and effectively accelerates the optimization speed to achieve the purpose of intelligent cross-organization large-scale optimization. The proposed method is applied to the production process of computer power in the electronics industry, and experimental results show the effectiveness of the proposed method.

关键词： Couplings NP-hard problem Electronics industry Decision making Collaboration Production Manufacturing

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Semi-supervised Graph-regularized Ridge Regression for Fault Diagnosis

Semi-supervised Graph-regularized Ridge Regression for Fault...

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第34届中国过程控制会议

作者： Deng Ruixiang Zhang Yingwei College of Information Science and Engineering Northeastern University State Laboratory of Synthetical Automation of Process Industries Northeastern University

Fault diagnosis is a crucial step in process *** existing fault diagnosis methods require sufficient fault samples with known fault information in training ***,the diagnoses of fault samples would cost considerable time and effort of *** is not convenient and economical to pay more attention to obtaining those fault samples with known fault information in preparation *** this paper,a new semi-supervised graph-regularized ridge regression(SGRR) is proposed for fault *** main contributions are summarized as follows:1) Only a few number of fault samples with known fault information are required in training stage.2) By analyzing the similarity and neighbor relationship among data,the most fault samples with unknown fault information in training dataset are diagnosed 3) The constructed model with certain parameters can be extended and applied on fault diagnosis of new *** results on the Tennessee Eastman process(TEP) verify the effectiveness and excellent performance of the proposed method.

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Fault Classification Method based on Self-paced Neighborhood Preserving Embedding

Fault Classification Method based on Self-paced Neighborhood...

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International Symposium on Autonomous Systems (ISAS)

作者： Hongrui Gao Chuan Ma Yingwei Zhang College of Information Science and Engineering Northeastern University Shenyang China State Laboratory of Synthesis Automation of Process Industry Northeastern University Shenyang China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

In view of the large amount of faulty data in industrial systems, strong correlation between data, large redundancy, and high dimensionality, traditional classification methods can easily lead to the phenomenon of "dimensionality disaster". On the basis of the Neighborhood Preserving Embedding algorithm (NPE), a fault classification algorithm based on Self-paced NPE is proposed. First, the neighbor point set and adjacency matrix of the fault sample points are obtained through the NPE algorithm. Secondly, the function of solving the projection matrix in the NPE algorithm is used as the loss function in the Self-paced Learning model to construct the objective function of the Self-paced Neighborhood Preserving Embedding (Self-paced NPE) algorithm. By designing the loss function in the Self-paced Learning model, gradually select from easy to difficult samples with smaller loss are selected, samples with larger loss are discarded, and relatively simple samples are used for training. Finally, the objective function of the Self-paced NPE algorithm is solved and the proposed algorithm is tested with TE process data . The experimental results show that, compared with the NPE algorithm, the Self-paced NPE algorithm can extract features of high-dimensional fault data more effectively, achieve dimension reduction, and improve the accuracy of fault classification.

关键词： Training Dimensionality reduction Manifolds Sensitivity Redundancy Filtering algorithms Feature extraction

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Distributed Fault-Tolerant Containment Control for Nonlinear Multi-Agent Systems Under Directed Network Topology via Hierarchical Approach

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IEEE/CAA Journal of Automatica Sinica 2021年第4期8卷 806-816页

作者： Shuyi Xiao Jiuxiang Dong the College of Information Science and Engineering Northeastern UniversityShenyang 110819 the State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819 the Key Laboratory of Vibration and Control of AeroPropulsion Systems Ministry of Education Northeastern UniversityShenyang 110819China

This paper investigates the distributed fault-tolerant containment control(FTCC)problem of nonlinear multi-agent systems(MASs)under a directed network *** proposed control framework which is independent on the global information about the communication topology consists of two *** from most existing distributed fault-tolerant control(FTC)protocols where the fault in one agent may propagate over network,the developed control method can eliminate the phenomenon of fault *** on the hierarchical control strategy,the FTCC problem with a directed graph can be simplified to the distributed containment control of the upper layer and the fault-tolerant tracking control of the lower ***,simulation results are given to demonstrate the effectiveness of the proposed control protocol.

关键词： Adaptive fault-tolerant control directed network topology distributed control hierarchical control multi-agent systems(MASs)

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Statistical process Monitoring Based on General Semi–Nonnegative Matrix Factorization

Statistical Process Monitoring Based on General Semi–Nonneg...

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International Symposium on Autonomous Systems (ISAS)

作者： Chuan Ma Yingwei Zhang College of Information Science and Engineering Northeastern University Shenyang China State Laboratory of Synthesis Automation of Process Industry Northeastern University Shenyang China

ISBN: (数字)9798350363173

ISBN: (纸本)9798350363180

Nonnegative matrix factorization (NMF) is a widely applied method for feature extraction and dimensionality reduction. However, existing NMF-like methods primarily focus on deriving a subspace representation based on partial bases from the original data, overlooking the inter-sample correlations. In this paper, a new method, named general semi–nonnegative matrix factorization (GSNMF), is proposed for statistical process monitoring. This method relieves the nonnegativity constraint on the original data, expanding its applicability, and is capable of capturing the primary variations in the data. Furthermore, by extracting the common features of the data in a low dimensional space, it preserves the specific and significant features of the data. Two test statistical metrics and kernel density estimation (KDE) are employed for fault detection. Finally, the superiority of the proposed method is validated by taking common public datasets as examples.

关键词： process monitoring Measurement Dimensionality reduction Correlation Fault detection Estimation Feature extraction

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Intelligent Manufacturing for the process Industry Driven by Industrial Artificial Intelligence

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engineering 2021年第9期7卷 1224-1230页

作者： Tao Yang Xinlei Yi Shaowen Lu Karl HJohansson Tianyou Chai State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China School of Electrical Engineering and Computer Science KTH Royal Institute of TechnologyStockholm 10044Sweden

Based on the analysis of the characteristics and operation status of the process industry,as well as the development of the global intelligent manufacturing industry,a new mode of intelligent manufacturing for the process industry,namely,deep integration of industrial artificial intelligence and the Industrial Internet with the process industry,is *** paper analyzes the development status of the existing three-tier structure of the process industry,which consists of the enterprise resource planning,the manufacturing execution system,and the process control system,and examines the decision-making,control,and operation management adopted by process *** on this analysis,it then describes the meaning of an intelligent manufacturing framework and presents a vision of an intelligent optimal decision-making system based on human–machine cooperation and an intelligent autonomous control ***,this paper analyzes the scientific challenges and key technologies that are crucial for the successful deployment of intelligent manufacturing in the process industry.

关键词： Industrial artificial intelligence Industrial Internet Intelligent manufacturing process industry

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Adaptive Safety-Certified Reinforcement Learning for Constrained Optimal Control of Autonomous Robots With Uncertainties

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IEEE Internet of Things Journal 2025年

作者： Zhang, Fei Yang, Guang-Hong Northeastern University College of Information Science and Engineering Liaoning Shenyang110819 China Northeastern University College of Information Science and Engineering State Key Laboratory of Synthetical Automation for Process Industries Liaoning Shenyang110819 China

This paper investigates a constrained optimal control problem for safety-critical robots with parametric uncertainties. A novel adaptive safety-certified reinforcement learning (RL) algorithm is proposed, leveraging control barrier functions (CBFs) to enable safe learning of the optimal policy during the online exploration phase. Specifically, a high-order robust adaptive CBF is presented to minimally adjust RL-derived control actions by incorporating a prescribed-time adaptation law to handle the unknown system parameters. This way directly enforces forward invariance, allowing the shrunken safe set to near the standard set within a user-prescribed time. Moreover, a novel adaptive critic learning frame is presented by introducing filtered auxiliary signals that integrate both instantaneous and historical data, which relaxes the strict persistent excitation (PE) condition required in the existing RL methods to a weaker, easily verifiable finite excitation (FE) condition. Later, a prescribed-time learning rule is developed to accelerate the convergence of weights. The key advantage of the proposed way is the decoupling of safety and RL convergence, enabling each component to be managed separately, thereby offering stronger safety certifications compared to the existing RL schemes even under uncertain dynamics. The effectiveness and superiority of the proposed scheme are proven via simulations for surveillance and regulation tasks of autonomous robots. © 2014 IEEE.

关键词： Adversarial machine learning

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Lateral-Longitudinal Prescribed-Time Cooperative Control of Vehicles Subject to Wear and Road Disturbance

Lateral-Longitudinal Prescribed-Time Cooperative Control of ...

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第43届中国控制会议

作者： Qian Zhang Ge Guo College of Information Science and Engineering Northeastern University State Key Laboratory of Synthetical Automation of Process Industries Northeastern University School of Control Engineering Northeastern University at Qinhuangdao

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper studies the lateral and longitudinal formation control issue of a collection of vehicles subject to wear and road disturbance.A novel prescribed-time disturbance observer is designed to estimate the unknown ***,based on the disturbance observer,an adaptive nonsingular vehicle formation control strategy is proposed to ensure the formation errors converge to a close neighborhood of origin in a prescribed time,which can be confirmed in advance by specifying several simple *** results validate the effectiveness of the presented control method.

关键词： Connected vehicles formation control disturbance observer prescribed time

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Design of remote group control system based on thermal environment of MODBUS launch vehicle 3

Design of remote group control system based on thermal envir...

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3rd International Conference on Intelligent Control, Measurement and Signal processing and Intelligent Oil Field, ICMSP 2021

作者： Li, Yijie Li, Hong Li, Pu Cheng, Ying School of Electronic Engineering Xi'An Shiyou University Automation Instrument and Process Control Laboratory Xi an China

ISBN: (纸本)9781665437158

Aiming at the problems of the ground simulation experiment of carrier rocket, such as the large number of regions divided, the different length of the device and the different model curve, the remote group control scheme of the rocket thermal environment was designed and realized. The system takes 108 sets of AC-DC conversion power electronic devices as the main power components, uses Ethernet Modbus TCP/IP communication protocol, and applies configuration software WinCC and S7-200 Smart PLC as the execution terminal. To be realized the monitoring of 108 AC - DC conversion power electronic equipment by a computer via multi-port switch. The system has been successfully applied in a research institute in Beijing, which improves the working efficiency and ensures the reliability and stability of the operation. © 2021 IEEE.

关键词： Rectifying circuits

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