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A New Self-Learning Optimization Management Scheme for Smart Grid systems

The International Journal of Intelligent control and systems 2024年第2期29卷 66-70页

作者： Qinglai Wei Zehua Liao School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

This paper presents a new energy optimization management scheme for the smart grid system(SGS),which considers not only the inclusion of renewable energy in energy management but also the feedback sale of redundant renewable energy to the grid,so as to obtain better optimization management results and avoid energy waste.A new performance index function is constructed,which aims to save users’electricity costs and protect energy storage *** construct a periodic iterative self-learning method based on the characteristics that the relevant data of SGS are approximately *** proposed self-learning optimization method is based on adaptive dynamic programming(ADP).The initial iterative control law is obtained by pre-training,and the designed method can be realized by neural *** experiments are carried out by using the relevant data of SGS for four *** experimental results show that the new energy management scheme can help users save a lot of electricity costs,and is more effective than some common methods.

关键词： Smart grid system energy management renewable energy self-learning adaptive dynamic programming

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H∞ state estimation for delayed neural networks via variable-augmented-based free-weighting matrices method

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Journal of the Franklin Institute 2025年第7期362卷

作者： Chang, Xu-Kang He, Yong School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

The issue of H∞ state estimation for neural networks with time-varying delays is investigated in this study. Firstly, an augmented Lyapunov-Krasovskii functional (LKF) with two delay-product-type terms is constructed to enhance the consideration of system state, delay, and delay derivative information. Furthermore, for taking into account more effective information, the LKF is augmented with both single and double integral variables. Accordingly, the LKF derivative becomes a higher-order term that exhibits nonlinear characteristics of the time delay. To solve the nonlinear problem, a variable-augmented-based free-weighting-matrices (VAFWMs) approach is employed to transform the nonlinear term into a linear form and provides more freedom in obtaining less-conservative results. Consequently, two improved H∞ state estimation criteria are derived. Lastly, a numerical example is provided to demonstrate the merits and effectiveness of the presented methods. Meanwhile, to prove the practical viability of the presented methods, this study extends the methods to a real-world quadruple-tank process system. © 2025 The Franklin Institute

关键词： Lyapunov functions

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An Improved Frequency Hopping Algorithm Based on Transmission Scheduling against Jamming Attacks 36

An Improved Frequency Hopping Algorithm Based on Transmissio...

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36th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2021

作者： Wang, Chenyuan Kong, Xiangying Chen, Xuebing Cao, Xianghui Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing210096 China Jiangsu Automation Research Institute Jiangsu China Southeast University School of Cyber Science and Engineering Nanjing China

ISBN: (纸本)9781665437127

In wireless networked systems, jamming attacks are destructive and easy to be launched. To mitigate the jamming attack impact, frequency hopping is an effective way, in which a defender side can switch channels to avoid using the ones under jamming attack. However, the resilient ability of anti-jamming of traditional frequency hopping algorithm can't meet the requirement of communication without channel strategy and jamming detection under the circumstance of various forms of jamming attacks. In this paper, an improved frequency hopping algorithm with higher transmit success rate (TSR) has been proposed based on channel selection and adjustment of transmission time to defend different kinds of attacks such as reactive jamming, static jamming and scanning jamming. Our algorithm judges whether to adjust data transmission time according to the result of transmit success rate and use channel selection strategy to avoid most of interfered channels. Finally, our proposed algorithm is evaluated as a resilient scheme under different forms of jamming attacks through simulations. © 2021 IEEE.

关键词： Frequency hopping

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Open-/Closed-loop Active Learning for Data-driven Predictive control

arXiv

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arXiv 2024年

作者： Feng, Shilun Shi, Dawei Shi, Yang Zheng, Kaikai The State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing100081 China The Department of Mechanical Engineering Faculty of Engineering University of Victoria VictoriaBCV8N 3P6 Canada

An important question in data-driven control is how to obtain an informative dataset. In this work, we consider the problem of effective data acquisition of an unknown linear system with bounded disturbance for both open-loop and closed-loop stages. The learning objective is to minimize the volume of the set of admissible systems. First, a performance measure based on historical data and the input sequence is introduced to characterize the upper bound of the volume of the set of admissible systems. On the basis of this performance measure, an open-loop active learning strategy is proposed to minimize the volume by actively designing inputs during the open-loop stage. For the closed-loop stage, an closed-loop active learning strategy is designed to select and learn from informative closed-loop data. The efficiency of the proposed closed-loop active learning strategy is proved by showing that the unselected data cannot benefit the learning performance. Furthermore, an adaptive predictive controller is designed in accordance with the proposed data acquisition approach. The recursive feasibility and the stability of the controller are proved by analyzing the effect of the closed-loop active learning strategy. Finally, numerical examples and comparisons illustrate the effectiveness of the proposed data acquisition strategy. Copyright © 2024, The Authors. All rights reserved.

关键词： Active learning

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Influence of Circuit Parameters on Discharge Characteristics and Shock-Wave in Underwater Electric Wire Explosion 16th

Influence of Circuit Parameters on Discharge Characteristics...

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16th Annual Conference of China Electrotechnical Society, ACCES 2021

作者： Yuan, Wei Han, Ruoyu He, Weisheng Li, Chen Cao, Yuchen Zhang, Yongmin School of Physics Beijing Institute of Technology Beijing100089 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China School of Electrical Engineering Xi’an Jiaotong University Xi’an710049 China

ISBN: (纸本)9789811915314

An experimental study on the underwater electrical wire explosion under microsecond-scale discharge was carried out. The electrophysical and shock-wave (SW) parameters of the circuit were measured under different stored energy and inserted inductance components. Specifically, the resistive load voltage, circuit current and SW pressure waveform were obtained, and the electric power and deposited energy of the load were calculated. Also, the peak pressure, full width at half maximum (thickness), and impulse of the SW were compared. The results showed that as the stored energy increased, the discharge mode would change. For a fixed wire load, increasing the stored energy would enhance the subsequent plasma expansion and produce a stronger SW. Furthermore, adding the inductance components could decrease the amplitude of current, voltage and electric power, affecting the strength of shape of the main SW. For the 1.3 μH inserted inductor, the peak of SW pressure would increase by about 8.7%, while for the 10.7 μH case, the peak would drop by about 5.1%. The phenomenon might be related to the stored energy of the circuit inductance. There should be an optimal matching relationship between the SW strength and the loop inductance. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Shock waves

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Trajectory tracking control strategy based on intelligent optimization for space underactuated manipulator

Trajectory tracking control strategy based on intelligent op...

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Industrial Cyber-Physical systems (ICPS)

作者： Houneng Wang Yong Hua Zixin Huang Ziang Wei Chengsong Yu Lejun Wang School of Electrical and Information Engineering Wuhan Institute of Technology Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications

For the space underactuated manipulator(SUM), this paper researches a intelligent optimization algorithm to plan the trajectory and design the tracking controller. The SUM system is composed of two planar underactuated sub-systems, which can realize horizontal and vertical movements respectively. The control target is to move the end point to the specified position, which means that all joints of the two sub-systems are controlled to the target state. For this control target, we design the feasible trajectory for the active links of the SUM by using particle swarm optimization(PSO) to achieve all joints reaching the specified target state simultaneously. Finally, we design the sliding mode variable structure controller for the active joints to track the planning trajectory. Based on the above control strategy, the control objective of the SUM is realized. The numerical simulation results demonstrate the effectiveness of the proposed control strategy.

关键词： Target tracking Trajectory tracking Trajectory planning Aerospace electronics Numerical simulation Manipulators Trajectory

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Multisensor fusion estimation of nonlinear systems with intermittent observations and heavy-tailed noises

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Science China(Information Sciences) 2022年第09期65卷 173-190页

作者： Bo XIAO Q.M.Jonathan WU Liping YAN School of Artificial Intelligence Beijing University of Posts and Telecommunications Department of Electrical and Computer Engineering University of Windsor Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Inspired by the robust student t-distribution based nonlinear filter(RSTNF), a student tdistribution and unscented transform(UT) based filter for state estimation of heavy-tailed nonlinear dynamic systems, a modified RSTNF for intermittent observations is derived. The fusion estimation for nonlinear multisensor systems with intermittent observations and heavy-tailed measurement and process noises is *** this work, the centralized fusion, the sequential fusion, and the na¨?ve distributed fusion algorithms are presented, respectively. Theoretical analysis shows that the presented algorithms are effective, which are the efficient extension of the classical unscented Kalman filter(UKF) or the cubature Kalman filter(CKF) based algorithms with Gaussian noises. Simulation results show that the presented algorithms are effective and feasible.

关键词： state fusion estimation nonlinear systems heavy-tailed noise intermittent observations multivariate t-distribution

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controllability analysis and stable control for planar non-one passive joint underactuated robot with bi-directional approach

Controllability analysis and stable control for planar non-o...

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第42届中国控制会议

作者： Zixin Huang Ziang Wei Wei Wang Xiangyu Gong Ba Zeng Lejun Wang School of Electrical and Information Engineering Wuhan Institute of Technology Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications

In this paper, we consider the controllability and stability control problem for planar underactuated robots with nonone passive joints. The dynamic constraints of the robot are mainly caused by nonholonomic constraints. Firstly, we establish the dynamic model of this system and analyze its controllability. Then, based on location and number of passive joints, we divide the system into different configurations. Next, we propose a stable control method based on bi-directional approach to achieve the stable control of different systems. At last, the numerical simulation conclusion illuminate the feasibility of this method.

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controllability Analysis and Stable control for Planar Non-One Passive Joint Underactuated Robot with Bi-Directional Approach

Controllability Analysis and Stable Control for Planar Non-O...

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Chinese control Conference (CCC)

In this paper, we consider the controllability and stability control problem for planar underactuated robots with non-one passive joints. The dynamic constraints of the robot are mainly caused by nonholonomic constraints. Firstly, we establish the dynamic model of this system and analyze its controllability. Then, based on location and number of passive joints, we divide the system into different configurations. Next, we propose a stable control method based on bi-directional approach to achieve the stable control of different systems. At last, the numerical simulation conclusion illuminate the feasibility of this method.

关键词：

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Semantic Segmentation of Indoor Point Clouds with the Channel Attention Mechanism

Semantic Segmentation of Indoor Point Clouds with the Channe...

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2022 Chinese Automation Congress, CAC 2022

作者： Liu, Wei Lu, Yisheng Zhang, Tao Chen, Jun School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geoexploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665465335

In recent years, the semantic segmentation of 3D point cloud has received increasing attention the field of computer vision, because 3D point cloud can better reflect our 3D space. Because of the unstructured and disordered characteristics of 3D point cloud data, semantic segmentation of point cloud is still a difficult task. Our network automatically learns the importance of feature channels by adding a channel attention module, which enables the network to obtain better training results. After the channel attention module is fused, the important channels in the features are enhanced, and the unimportant channels are suppressed, making the network training more efficient. In this paper, we propose an indoor point cloud semantic segmentation method combined with channel attention mechanism. The experimental results show that our method achieves better results than other methods. © 2022 IEEE.

关键词： Semantic Segmentation

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