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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...

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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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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Billet Number Recognition Based on ESRGAN and Improved YOLOv5 37

Billet Number Recognition Based on ESRGAN and Improved YOLOv...

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37th Youth Academic Annual Conference of Chinese Association of automation, YAC 2022

作者： Wang, Zijia Dong, Yichao Niu, Dan Liu, Minghao Li, Qi Chen, Xisong Ministry of Education School of Automation Nanjing China Ministry of Education School of Automation Key Laboratory of Measurement and Control of CSE Nanjing China Nanjing Sciyon Wisdom Technology Group Co. Ltd. Nanjing211102 China Jiangsu Province Key Laboratory of Thermal Process Intelligent Control Nanjing211102 China

ISBN: (纸本)9781665465366

Aiming at solving the problem of billet number recognition and further improve the rate of recognition, this paper proposes a billet number recognition algorithm based on ESRGAN and improved YOLOv5, which is referred to as YOLOv5-Billet in this paper. According to the actual situation, we propose a target recognition algorithm that uses the lightweight network MobileNetv3 to replace the backbone feature extraction network of YOLOv5. We also introduce ESRGAN to improve the quality of the input image and further improve the recognition effect. A series of rigorous experiments show that YOLOv5-Billet has a certain improvement in billet recognition speed and precision. Specifically, the average precision of YOLOv5-Billet is improved by 10.8%, and the detection speed is also improved by 5.12fps, reaching 40.35fps. Through the experimental verification of real-time collection of data sets, compared with a variety of classical target detection methods, the recognition precision and detection speed are improved to varying degrees. This model maintains the lightweight characteristics of YOLOv5 and meets the requirements of real-time monitoring of the number of blanks. © 2022 IEEE.

关键词： Image enhancement

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Iterative Learning Hybrid Robust Predictive control for Multi-Phase Batch processes with Asynchronous Switching via a Lyapunov-Razumikhin Approach

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2023年 1卷 345-358页

作者： Li, Hui Wang, Shiqi Shi, Huiyuan Li, Ping Su, Chengli School of Electronics and Information Engineering University of Science and Technology Liaoning Anshan114051 China School of Information and Control Engineering Liaoning Petrochemical University Fushun113001 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Information Engineering Liaodong University Dandong118001 China

For a class of the industrial cyber-physical system, i.e., multi-phase batch processes with small time-delays and asynchronous switching, this study develops a two-dimensional iterative learning hybrid robust predictive control method. Compared with the previous Lyapunov-Krasovsky function-based method, stability conditions given by the Lyapunov-Razumikhin function-based method is less conservative intensive in dealing with small time-delays. Not only that, compared to the traditional iterative learning method, the rolling-optimized gains of the control law make it possible for the designed controller to have fewer learning cycles, and the control performance is even better. Meanwhile, the minimum and the maximum dwelling times are obtained in conjunction with the exponential stability analysis of the system. Since the obtained dwelling times, an advanced switching signal is provided to avoid asynchronous switching situations. The simulation results for the injection molding process are finally utilized to illustrate the effectiveness and feasibility of the developed approach. © 2023 The Authors.

关键词： Time delay

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Neural learning control for discrete-time nonlinear systems in pure-feedback form

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Science China(Information Sciences) 2022年第2期65卷 124-138页

作者： Min WANG Haotian SHI Cong WANG Jun FU School of Automation Science and Engineering South China University of Technology School of Control Science and Engineering Shandong University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University

This study focuses on state-feedback and output-feedback neural learning control problems for discrete-time nonlinear systems in the pure-feedback form. First, an extended result for the exponential stability for a class of discrete-time linear time-varying(LTV) systems with n-step delays is proposed to verify the exponential convergence of estimated weights. Subsequently, both state-feedback and outputfeedback adaptive neural network(NN) controllers are constructed by combining the classical n-step and n-step input-output predictors. After ensuring convergence of the system output to a recurrent reference signal, the radial basis function subvector of NN is verified to satisfy the persistent exciting condition using the system state equation and the implicit function theorem. By combining the extended stability corollary of an LTV system, the estimated weights are verified to exponentially converge to their optimal values. By constructing "learning rules" and using a "mod" function, the estimated weights with a convergent sequence are synthetically represented and stored as the experience knowledge, which is reused to construct neural learning controllers. The proposed neural learning controllers not only accomplish similar control tasks but also reduce the burden of online computation compared with the conventional adaptive NN ***, simulation results are presented to demonstrate the effectiveness of the presented schemes.

关键词： discrete-time nonlinear systems pure-feedback systems learning control neural networks persistent excitation

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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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Finite-Time Adaptive Quantized control of Switched Constrained Nonlinear Systems

Finite-Time Adaptive Quantized Control of Switched Constrain...

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IEEE International Conference on Cyber Technology in automation, control, and Intelligent Systems

作者： Penghao Chen Xiaoli Luan Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

In this paper, the finite-time adaptive control issue is addressed for a class of switched strict-feedback nonlinear systems with input quantization and output constraints. Firstly, the barrier Lyapunov function is introduced to cope with statistic output constraints, and with the help of Young's inequality, only one learning parameter of neural networks needs to be tuned online at each step of recursion. Then, a hysteresis quantizer is introduced to handle the input signal. Finally, by appropriately choosing the initial value of the switched subsystem and using the characteristics of dynamic surface control, finite-time adaptive neural quantized control is designed to guarantee that all signals are semi-globally practical finite-time stable. Simulation results verify the effectiveness of the proposed means.

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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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Data-Driven Distributionally Robust Planning of Energy Hub Coupled with Carbon Capture Utilization and Storage Facilities 42

Data-Driven Distributionally Robust Planning of Energy Hub C...

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42nd Chinese control Conference, CCC 2023

作者： Ma, Xutao Ning, Chao Shanghai Jiao Tong University Department of Automation Shanghai200240 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9789887581543

Toward carbon peaking and carbon neutrality goals in China, a transition from traditional fossil power to renewable energy becomes an imperative need. This paper aims to address the planning problem of a highly renewable-energy penetrated energy hub system, coupled with carbon capture facilities and downstream production processes of hydrogen and methanol, under the uncertainty of renewable power output. To this end, we propose a two-stage distributionally robust optimal planning model, where investment decisions are the first-stage variables and operation variables are determined at the second stage after the realization of uncertainty. In the proposed model, we utilize historical data samples to construct a strengthened ambiguity set that leverages both Wasserstein distance and moment information for a better characterization of renewable generation uncertainty. Moreover, to efficiently solve the proposed planning problem, we develop a simplified affine decision rule method in a general setting with both moment and Wasserstein ambiguity, and then apply it to reformulate the distributionally robust planning problem. The derived reformulation possesses the favorable property that its scale is free from the sample size, thus greatly reducing the computational complexity. Computational results validate the effectiveness of the proposed planning model and the computational efficiency of the solution methodology. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Carbon capture

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Experience Replay Q(λ)-learning with Leader-Following control for Multi-Evader Pursuit Evasion Games 5

Experience Replay Q(λ)-learning with Leader-Following Contr...

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5th IEEE Information Technology, Networking, Electronic and automation control Conference, ITNEC 2021

作者： Zhu, Zhe-Yang Liu, Cheng-Lin Jiangnan University Key Laboratory of Advanced Process Control for Light Industry Institute of Automation Wuxi214122 China

ISBN: (纸本)9781665415989

This paper addresses a pursuit evasion game with multi-evader, and only some pursuers which are termed as leading pursuers can access the positions of the evaders during the pursuit. Furthermore, Q(λ)-learning is utilized to train the pursuers. Because Q(λ)-learning exhibits slow convergence, a new method that combines experience replay Q(λ)-learning and dynamic target assignment is introduced. Simulation shows that the proposed method achieves better convergence results than Q(λ)-learning in our multi-evader pursuit evasion game. © 2021 IEEE.

关键词： Reinforcement learning

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