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Adaptive Consensus Quantized control for a Class of High-Order Nonlinear Multi-Agent Systems With Input Hysteresis and Full State Constraints

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1574-1589页

作者： Guoqiang Zhu Haoqi Li Xiuyu Zhang Chenliang Wang Chun-Yi Su Jiangping Hu the School of Automation Engineering Northeast Electric Power UniversityJilin 132012 the Jilin Province International Research Center of Precision Drive and Intelligent Control Jilin 132012China the School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China the Department of Mechanical and Industrial Engineering Concordia UniversityQCMontrealH3B 1R6Canada the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China(

For a class of high-order nonlinear multi-agent systems with input hysteresis,an adaptive consensus output-feedback quantized control scheme with full state constraints is *** major properties of the proposed control scheme are:1)According to the different hysteresis input characteristics of each agent in the multi-agent system,a hysteresis quantization inverse compensator is designed to eliminate the influence of hysteresis characteristics on the system while ensuring that the quantized signal maintains the desired value.2)A barrier Lyapunov function is introduced for the first time in the hysteretic multi-agent *** constructing state constraint control strategy for the hysteretic multi-agent system,it ensures that all the states of the system are always maintained within a predetermined range.3)The designed adaptive consensus output-feedback quantization control scheme allows the hysteretic system to have unknown parameters and unknown disturbance,and ensures that the input signal transmitted between agents is the quantization value,and the introduced quantizer is implemented under the condition that only its sector bound property is *** stability analysis has proved that all signals of the closed-loop are semi-globally uniformly *** Star Sim hardware-in-the-loop simulation certificates the effectiveness of the proposed adaptive quantized control scheme.

关键词： Adaptive quantized control barrier Lyapunov function input hysteresis multi-agent systems

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Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

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Computer Modeling in engineering & Sciences 2023年第12期137卷 2163-2192页

作者： Ali S.Alghamdi Mohana Alanazi Abdulaziz Alanazi Yazeed Qasaymeh Muhammad Zubair Ahmed Bilal Awan M.G.B.Ashiq Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakaka72341Saudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityAr’Ar73222Saudi Arabia Automation and Control Department College of Engineering TechnologyUniversity of Doha for Science and TechnologyDoha24449Qatar Department of Electrical and Computer Engineering College of Engineering and Information TechnologyAjman UniversityAjman20550United Arab Emirates Department of Physics College of ScienceImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried *** has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the *** standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight *** proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PSO),and salp swarm algorithm(SSA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub ***,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

关键词： Stochastic energy hub scheduling energy profit uncertainty Hong’s two-point estimate method improved artificial rabbits optimization

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Intermittent control for Fixed-Time Synchronization of Coupled Networks

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IEEE/CAA Journal of Automatica Sinica 2023年第6期10卷 1488-1490页

作者： Yongbao Wu Ziyuan Sun Guangtao Ran Lei Xue the School of Automation Southeast UniversityNanjing 210096China the Department of Applied Mathematics University of WaterlooOntario N2J 4N3Canada the Department of Control Science and Engineering Harbin Institute of TechnologyHarbin 150001China

Dear Editor, This letter deals with fixed-time synchronization(Fd-TS) of complex networks(CNs) under aperiodically intermittent control(AIC)for the first time. The average control rate and a new Lyapunov function are ... 详细信息

关键词： synchronization Synchronization overcome

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Nonlinear Model Predictive control of Quadrotor Using Direct Multiple Shooting

Nonlinear Model Predictive Control of Quadrotor Using Direct...

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International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Pham Duc Dai Bui Thi Hai Linh Department of Control Engineering and Automation Thuyloi University Hanoi Vietnam

ISBN: (数字)9798350371154

ISBN: (纸本)9798350371161

Quadrotors have been applied to many areas. control of the quadrotor for tracking the desired trajectory is challenging. Several traditional control approaches using PID controllers have been applied to control UAV. Such the approach requires the model to be linearized. This paper proposed to apply the nonlinear model predictive control to guide the quadrotor while getting collision free by using the concept of the hyperplane moving constraints. To address the NMPC, the multiple shooting method has been applied to discretize the optimal control problem to the nonlinear program (NLP) and it is efficiently solved by the standard NLP solver. Numerical computation has been shown that the application of the multiple shooting method gives the more efficient NLP with a less number of optimization variables.

关键词： Trajectory tracking Optimal control Water quality Autonomous aerial vehicles Real-time systems Trajectory Optimization

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Dynamic Quantized control of Fuzzy Semi-Markov Jump Systems With Fading Channels: An Improved Event-Triggered Mechanism

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3519-3531页

作者： Hu, Meng-Jie Park, Ju H. Cheng, Jun Wang, Yan-Wu China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Yeungnam University Department of Electrical Engineering Gyeongsan38541 Korea Republic of Guangxi Normal University School of Mathematics and Statistics Guilin541006 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China

This article focuses on the dynamic quantized control for Takagi-Sugeno fuzzy semi-Markov jump systems (T-S FSMJSs) under fading channels and deception attacks, employing an improved event-triggered mechanism (ETM) strategy. Specifically, a more generalized semi-Markov process (SMP) that is governed by a higher-level deterministic switching signal (HLDSS) is addressed. A novel dynamic ETM is skillfully developed based on the information of quantization and two internal dynamic adjusting variables to further enhance the network bandwidth utilization. The dual asynchronous phenomenon between the plant and controller (asynchronous modes and mismatched premise variables) is addressed. This implies that the designed controller is not required to share the same membership functions and modes as the plant, establishing a more rational structure. The hidden semi-Markov model (HSMM) is attained to characterize the stochastic varying channel fading amplitudes. The Lyapunov function incorporating mode and fuzzy information is constructed to establish sufficient criteria ensuring the strictly dissipative performance and mean-square exponential stability (MSES) of the resulting closed-loop systems, and a new security fuzzy dual asynchronous controller is then developed. Finally, the efficacy and applicability of the results are demonstrated through numerical and practical examples. © 2025 IEEE.

关键词： Membership functions

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The Deployment of Microservice at Edge based on MQTT for Low Latency 22

The Deployment of Microservice at Edge based on MQTT for Low...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Han, Mengqi Yang, Bo Liu, Yuxiang Liu, Sicheng Liu, Qi Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798331527471

With the rapid development of smart manufacturing, existing microservice deployment strategies based on the TCP protocol tend to encounter problems such as network latency, excessive header length, and port exhaustion in high concurrency scenarios. MQTT Broker can relay data between microservices, effectively alleviating these issues. However, the communication overhead of the Broker is significantly related to its deployment and the dependency of microservices. An appropriate deployment solution can significantly improve service quality. To address this issue, this paper models the deployment of MQTT Broker and microservices as a graph with cycles. By introducing auxiliary variables, the NP-hard problem is transformed into a mixed-integer quadratic programming problem, improving problem-solving efficiency and optimizing the microservices deployment strategy to reduce communication overhead. Meanwhile, a real-world heterogeneous cluster was constructed to experiment on fault detection applications, elaborating on the superiority of the microservice deployment strategy designed in this paper. Experimental results demonstrate that our approach reduces communication overhead by 20% in comparison to both the greedy strategy and the K8s strategy. This suggests that achieving an optimal balance between the number of Brokers and microservices is vital for ensuring efficient resource utilization and maintaining low communication latency, particularly as the scale of services expands. © 2024 IEEE.

关键词： Smart manufacturing

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Two-Stage OD Flow Prediction for Emergency in Urban Rail Transit

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IEEE Transactions on Intelligent Transportation Systems 2024年第1期25卷 920-928页

作者： Zhu, Guangyu Ding, Jiacun Wei, Yun Yi, Yang Xu, Sendren Sheng-Dong Wu, Edmond Q. Beijing Jiaotong University Key Lab. of Transport Industry of Big Data Application Technologies for Comprehensive Transport The Beijing Research Center of Urban Traffic Information Sensing and Service Technologies Beijing100044 China Beijing Mass Transit Railway Operation Corporation Ltd. Beijing100014 China Yangzhou University College of Information Engineering Yangzhou225127 China National Taiwan University of Science and Technology Automation and Control Center The Graduate Institute of Automation and Control Taipei106335 Taiwan Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China The Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China

Urban rail transit (URT) is vulnerable to natural disasters and social emergencies including fire, storm and epidemic (such as COVID-19), and real-time origin-destination (OD) flow prediction provides URT operators with important information to ensure the safety of URT system. However, hindered by the high dimensionality of OD flow and the lack of supportive information reflecting the real-time passenger flow changes, study in this area is at the beginning stage. A novel model consisting of two stages is proposed for OD flow prediction. The first stage predicts the inflows of all stations by Long Short-Term Memory (LSTM) in real time, where the dimension is reduced compared with predicting OD flows directly. In the second stage, the notion of separation rate, namely, the proportion of inbound passengers bounding for another station, is estimated. Finally, The OD flow is predicted by multiplying the inflow and separation rate. Experiments based on Hangzhou Metro dataset show the proposed model outperforms the contrast model in weighted mean average error (WMAE) and weighted mean square error (WMSE). Results also suggest that the proposed prediction model performs better on weekdays than on weekends, and with greater accuracy on larger OD flows. © 2000-2011 IEEE.

关键词： Forecasting

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Supervised-learning guarantee for quantum AdaBoost

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Physical Review Applied 2024年第5期22卷 054001页

作者： Yabo Wang Xin Wang Bo Qi Daoyi Dong Key Laboratory of Systems and Control Beijing 100049 People’s Republic of China Department of Automation School of Engineering

In the noisy intermediate-scale quantum (NISQ) era, the capabilities of variational quantum algorithms are greatly constrained due to a limited number of qubits and the shallow depth of quantum circuits. We may view these variational quantum algorithms as weak learners in supervised learning. Ensemble methods are general approaches to combining weak learners to construct a strong one in machine learning. In this paper, by focusing on classification, we theoretically establish and numerically verify a learning guarantee for quantum adaptive boosting (AdaBoost). The supervised-learning risk bound describes how the prediction error of quantum AdaBoost on binary classification decreases as the number of boosting rounds and sample size increase. We further empirically demonstrate the advantages of quantum AdaBoost by focusing on a 4-class classification. The quantum AdaBoost not only outperforms several other ensemble methods, but in the presence of noise it can also surpass the ideally noiseless but unboosted primitive classifier after only a few boosting rounds. Our work indicates that in the current NISQ era, introducing appropriate ensemble methods is particularly valuable in improving the performance of quantum machine learning algorithms.

关键词： Quantum algorithms & computation Quantum circuits Supervised learning

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On non-von Neumann flexible neuromorphic vision sensors

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npj Flexible Electronics 2024年第1期8卷 638-663页

作者： Hao Wang Bin Sun Shuzhi Sam Ge Jie Su Ming Liang Jin Institute for Future Shandong Key Laboratory of Industrial Control TechnologySchool of AutomationQingdao UniversityQingdao 266071China College of Electronic and Information Engineering Qingdao UniversityQingdao 266071China Department of Electrical and Computer Engineering and Institute for Functional Intelligent MaterialsNational University of SingaporeSingapore 117583Singapore

The structure andmechanismof thehuman visual system contain rich treasures,and surprising effects can be achieved by simulating the human visual *** this article,starting from the human visual system,we compare and discuss the discrepancies between the human visual system and traditional machine vision *** the wide variety and large volume of visual information,the use of nonvon Neumann structured,flexible neuromorphic vision sensors can effectively compensate for the limitations of traditional machine vision systems based on the von Neumann ***,this article addresses the emulation of retinal functionality and provides an overview of the principles and circuit implementation methods of non-von Neumann computing ***,in terms of mimicking the retinal surface structure,this article introduces the fabrication approach for flexible sensor ***,this article analyzes the challenges currently faced by non-von Neumann flexible neuromorphic vision sensors and offers a perspective on their future development.

关键词： Neumann system starting

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Model predictive control of hemodynamics during intravenous general anesthesia 27

Model predictive control of hemodynamics during intravenous ...

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27th International Conference on System Theory, control and Computing, ICSTCC 2023

作者： Farbakhsh, Hamed Yumuk, Erhan Othman, Ghada Ben De Keyser, Robin Copot, Dana Birs, Isabela Ionescu, Clara M. Ghent University Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Tech Lane Science Park 125 Zwijnaarde9052 Belgium Istanbul Technical University Department of Control and Automation Engineering Istanbul Turkey Technical University of Cluj-Napoca Department of Automation Memorandumului no. 28 Cluj-Napoca400114 Romania

ISBN: (纸本)9798350337983

In the operating rooms and the intensive care unit, it is crucial to manage the patient's hemodynamic status, which includes factors like cardiac output and mean arterial pressure. Anesthesiologists confront a difficult task while monitoring high-risk patients. Cardiac output optimization has been found to enhance the result of high-risk patients in terms of hospital stay, mortality rate, post-operative problems, etc. The application of standard control approaches is restricted because the mean arterial pressure response of a patient using vasoactive medicines is modeled by a first-order dynamical system with time-varying parameters and a time-varying delay in the control input. In order to circumvent implementation challenges, this work develops an approximation technique that describes the system using a higher-order model. Predictive control is therefore used to comprehend the practical application of higher-order hemodynamic systems. The effectiveness of this strategy is demonstrated by the simulations and outcomes that are given. © 2023 IEEE.

关键词： Model predictive control

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