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IEEE International Conference on Unmanned systems (ICUS)

作者： Xiubin Chen Lei Zhang Fang Xu Weiran Yao School of Astronautics Harbin Institude of Technology Harbin China Wuhan 2nd Ship Design and Research Institute Wuhan China Marine Military Intelligence Innovation Institute CSSC Systems Engineering Research Institute Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

Traditional task allocation methods for unmanned swarm systems ignore the effects of actual paths, resulting in estimation accuracy reduction. This paper formulates task planning problem by incorporating physical and logical constraints, and establishes an integrated framework of task allocation and path planning. Conflict-based search method is used to address path planning with physical constraints. A genetic algorithm is employed to solve multi-traveling salesman allocation problem. A bounded suboptimal optimization, a data dictionary, and an island model are introduced to accelerate the convergence speed of the genetic algorithm. The experiments verify that compared to the decoupled task planning methods, the proposed method improves task execution efficiency and remains adaptability to various complex spatial maps.

关键词： Dictionaries Search methods Estimation Path planning Data models Planning Resource management Optimization Genetic algorithms Convergence

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Economic research on User-Side Photovoltaic Energy Storage System Considering Shared Energy Storage

Economic Research on User-Side Photovoltaic Energy Storage S...

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International Conference on Power and Energy Technology (ICPET)

作者： Kaiwen Chen Qingyi Wang Kai Kang Hao Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China PowerChina Hubei Electric Engineering co. LTD Wuhan China Wuhan Second Ship Design and Research Institute Wuhan China

Based on the background of photovoltaic development in the whole county and the demand for energy storage on the user-side, this paper establishes an economic evaluation model of user-side photovoltaic energy storage system considering shared energy storage. Firstly, three schemes of no energy storage, independent energy storage and shared energy storage are proposed, and the influence of photovoltaic energy storage system loss on annual power generation is considered. Secondly, based on the whole life cycle theory, the cost and benefit model of the user-side photovoltaic energy storage system is established, and the unit electricity cost of the user is used as the evaluation index. Finally, the relevant data of user in Hubei area are analyzed as an example to verify the effectiveness of the model and provide reference for the investment of related projects.

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Double deep Q-learning for anti-saturation attack problem of warship group 1

Double deep Q-learning for anti-saturation attack problem of...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Li, Wei Xiong, Gang Tao, Hao Han, Yunjun Wang, Fang Dong, Xisong Shen, Zhen Institute of Automation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences China China Ship Development and Design Center Wuhan430064 China Shandong University Jinan China

ISBN: (纸本)9781665433372

Anti-saturation attack (ASA) strategy is vital for the survival of a warship group, and attracts the focus of many researchers. In this paper, the dynamics of ASA is formulated as a Markov Decision Process (MDP) with an enhanced states space since those characters are involved, such as the formation and detection and interception areas of warship group. A reinforcement learning method (Double Deep Q-leaning, DDQN) is developed to solve the problem and deal with the curse of dimensionality whereby the cost-to-go value is calculated by a marine engagement simulation system. A heuristic defense algorithm guided by field expert knowledge is designed for comparison. The experimental results show that the DDQN method performs better in anti-saturation attack scenarios. © 2021 IEEE.

关键词： Reinforcement learning

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Urban trip generation forecasting based on gradient boosting algorithm 1

Urban trip generation forecasting based on gradient boosting...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Li, Zhishuai Xiong, Gang Zhang, Yu Zheng, Meng Dong, Xisong Lv, Yisheng Institute of Automation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Municipal Institute of City Planning and Design Traffic Planning Department Beijing China

ISBN: (纸本)9781665433372

The four-step transportation model plays an important role in urban planning. The quality of the first phase, i.e. trip generation, determines the performance of the global course. The majority of trip generation forecasting models highly rely on mathematical derivation and have many predictor variables during the prediction, which leads to low accuracy of results and requires laboriously hand-crafted design of input vectors. This paper is the first to introduce the gradient boosting decision tree (GBDT) algorithm for trip generation prediction, and harmonizes such a powerful machine learning method with traditional urban planning requirements to achieve better prediction performance. Unlike the commonly used linear regression method, GBDT can automatically perform feature selection and model the non-linear relationships between input and output variables. Experimental results on real-world residential travel census in Beijing prove that the GBDT model significantly outperforms the baseline and can forecast the trip generation more accurately. © 2021 IEEE.

关键词： Decision trees

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Stability analysis of linear systems with two additive time-varying delays via the extended reciprocally convex matrix inequality

Stability analysis of linear systems with two additive time-...

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第40届中国控制会议

作者： Chen Yan Chuan-Ke Zhang Xi-Zi Zhou School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Art and Design Wuhan University of Technology

This paper investigates the stability of linear systems with two additive time-varying delays. Firstly, an augmented Lyapunov-Krasovskii functional(LKF) is constructed by introducing a novel augmented term which contains the derivative of state vector into integral terms. Then the extended reciprocally convex matrix inequality together with the Wirtinger integral inequality is used to estimate the derivative of the proposed LKF. As a result, a stability criterion with less conservatism is established. Finally, the advantage of the stability criterion is demonstrated through a numerical example and the application of the stability criterion to stability analysis of load frequency control is illustrated.

关键词： linear system additive time-varying delays stability analysis reciprocally convex matrix inequality

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Limit-Cycle-Based design of Formation control for Mobile Agents

Limit-Cycle-Based Design of Formation Control for Mobile Age...

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作者： Wang, Chen Xia, Weiguo Xie, Guangming National Engineering Research Center for Software Engineering Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian116024 China State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

In this article, we study the formation problem for a group of mobile agents in a plane, in which the agents are required to maintain a distribution pattern, as well as to rotate around or remain static relative to a static/moving target. The prescribed distribution pattern is a class of general formations where the distances between neighboring agents or the distances between each agent and the target do not need to be equal. Each agent is modeled as a double integrator and can merely perceive the relative information of the target and its neighbors, and the acceleration of the target. In order to solve the formation problem, a limit-cycle-based controller design is delivered. We divide the overall control objective into two subobjectives, where the first is target circling that each agent keeps its own desired distance to the static/moving target as well as rotating around or remaining static relative to the target as expected, and the second is distribution adjustment that each agent maintains the desired distance to its neighbors. Then, we propose a controller comprised of two parts, where a limit cycle oscillator named a converging part is designed to deal with the first subobjective, while a layout part is introduced to address the second subobjective. One key merit of the controller is that it can be implemented by each agent in its local frame so that only local information is utilized without knowing global information. Theoretical analysis of the convergence to the desired formation, of which the agents are required to be evenly distributed on a circle around the target, is provided for the multiagent system under the proposed controller. Numerical simulations are given to validate the effectiveness of the proposed controller for the cases of general formations, and to show that no collision between agents ever takes place throughout the system's evolution. © 1963-2012 IEEE.

关键词： Multi agent systems

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A Memristor Based Chaotic Oscillator for Weak Signal Detection and Its Circuitry Realization

Research Square

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research Square 2021年

作者： Dong, Kaifeng Xu, Kun Zhou, Youyou Zuo, Chao Wang, Leimin Zhang, Chuanke Jin, Fang Song, Junlei Mo, Wenqin Hui, Yajuan 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 Wuhan Second Ship Design and Research Institute Wuhan430064 China

A new type of weak signal detection system that combines the memristor and Van der pol-Duffing chaotic system has been proposed in this paper, and the dynamic characteristics of the system are studied. It is observed that the system can change from a chaotic state to a periodic state under different driving force amplitudes. Moreover, as compared with several classical chaotic oscillators, the numerical simulation results show that the system has stronger anti-noise performance with the detectable signal-to-noise ratio reaches -163dB, and has a wider detection range. Its detection accuracy is up to 1 × 10−9. More importantly, this paper provides the circuit implementation scheme of the system, and the weak signal can be detected with our designed circuit. This may offer a possible way for weak signal detection system with good performance in anti-noise performance, detection range and accuracy. © 2021, CC BY.

关键词： Memristors

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Fault Diagnosis of Micro Grid Inverter Based on Wavelet Transform and Probabilistic Neural Network

Fault Diagnosis of Micro Grid Inverter Based on Wavelet Tran...

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第三十九届中国控制会议

作者： Xin Gong Nan Wang Yiqiong Zhang Shuai Yin Mingyang Wang Genping Wu School of Automation China University of Geosciences (Wuhan) Hubei Provincial Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Second Ship Design and Research Institute

This paper focuses on the fault diagnosis of IGBT switch for microgrid three-phase inverters. Based on the analysis of all kinds of fault mechanisms, firstly, the fault simulation model of microgrid inverter is built on MATLAB/Simulink to simulate the fault state of inverter switch under various faults. The load-side three-phase current fault data is collected. Then, wavelet transform is used to extract feature parameters, and normalize the process in the form of energy to construct the fault feature vector. Finally, the genetic algorithm-based probability neural network(PNN) is used for classification. The experimental results show that the method that combining wavelet transform and PNN can diagnose the faults of microgrid inverter accurately and effectively.

关键词： Inverter Fault diagnosis Wavelet transform Genetic algorithm Probabilistic neural network

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Double Deep Q-learning for Anti-saturation Attack Problem of Warship Group

Double Deep Q-learning for Anti-saturation Attack Problem of...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Wei Li Gang Xiong Hao Tao Yunjun Han Fang Wang Xisong Dong Zhen Shen State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences China China Ship Development and Design Center Wuhan China School of Control Science and Engineering (CSE) Shandong University Jinan China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China

关键词： Industries Heuristic algorithms Digital twin Conferences Knowledge based systems Reinforcement learning Markov processes

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Urban Trip Generation Forecasting Based on Gradient Boosting Algorithm

Urban Trip Generation Forecasting Based on Gradient Boosting...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Zhishuai Li Gang Xiong Yu Zhang Meng Zheng Xisong Dong Yisheng Lv State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Municipal Institute of City Planning and Design Beijing China

关键词： Machine learning algorithms Urban planning Transportation Predictive models Prediction algorithms Feature extraction Boosting

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