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作者： Mu, Qin Li, Nanxi Chen, Cong Wei, Xiaozheng Wen, Rong Wu, Muqing Li, Xiang Liu, Ying School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China National Key Lab of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu China School of Network and Communication Engineering Chengdu Technological University Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

Using a large number of power amplifiers brings serious nonlinear distortion to 5G communication systems, which becomes a challenging problem for conventional digital predistortion (DPD) to linearize signals. To address this challenge, we propose a digitally assisted nonlinearity suppression architecture for applications in multiple antenna arrays. In this architecture, we use an auxiliary array to generate a nonlinear cancelation signal to cancel with the main beam at the receiving end. We explore a two-step method to model the nonlinear signal and combine neural network to complete the modeling. In addition, we introduce a novel method for estimating and tracking the channel to update the model coefficients. To verify the proposed methods, we design a scene and compare the performance of our architecture with that of conventional DPD. Our experiments demonstrate that our proposed methods can significantly enhance the adjacent channel power leakage ratio performance by 12 dB while also optimizing in-band distortion. Moreover, our architecture outperforms conventional DPD approaches even with enhanced distortion. © 2023 John Wiley & Sons Ltd.

关键词： Power amplifiers

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Mobilenetv2-SSD Target Detection Method Based on Multi-scale Feature Fusion 8th

Mobilenetv2-SSD Target Detection Method Based on Multi-scale...

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8th International Conference on Cognitive Systems and Information Processing, ICCSIP 2023

作者： Li, Boao Jiang, Du Tang, Xinjie Sun, Ying Weng, Yaoqing Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China Hubei Longzhong Laboratory Hubei Xiangyang441000 China

ISBN: (纸本)9789819980208

Most of the deep learning networks used in target detection algorithms are very complex, which poses difficulties for edge devices with limited storage capacity and computing power, such as mobile terminals. A MobileNetv2-SSD target detection algorithm based on multi-scale feature fusion is proposed in this paper. We use MobileNetv2 to improve the SSD algorithm by replacing the original network’s backbone network VGG16 with the lightweight network MobileNetv2 to perform the model streamlining. The problem of accuracy loss due to model compression is improved by the designed feature fusion module and finally tested on the dataset. The experimental results show that the mAP and FPS are 90.37% and 50FPS, respectively, and the detection accuracy is improved by 3.24% compared with the original SSD network, the detection speed is 1.9 times of the original one, and the size of the model is only 28.5M, which is only 30.5% of the original model. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computer vision

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Demand-Side Frequency control in Power Network Based on Multi-Agent Deep Reinforcement Learning 5

Demand-Side Frequency Control in Power Network Based on Mult...

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5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Liu, Xianggang Liu, Zhi-Wei Chi, Ming Zhang, Yifan Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education College of Artificial Intelligence and Automation Wuhan China

ISBN: (纸本)9798350325294

The integration of renewable energy sources into the power grid has led to new challenges in maintaining the stability of the system frequency. This paper proposes a novel approach to address the Optimal Demand Side Frequency control (ODFC) problem using Multi-Agent Deep Deterministic Policy Gradient (MADDPG) method. The proposed method models the ODFC problem as a Markov game, with centralized training based on multi-agent cooperative self-learning and associative storage service. In the decentralized execution stage, each agent independently outputs control actions to the controlled plant using local observations. Numerical simulations show that the proposed method effectively addresses the ODFC problem with superior performance compared to traditional methods. © 2023 IEEE.

关键词： Numerical methods

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UAV-Aided Localization and Communication: Joint Frame Structure, Beamwidth, and Power Allocation

IEEE Journal of Selected Areas in Sensors

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IEEE Journal of Selected Areas in Sensors 2024年 1卷 154-165页

作者： Liang, Tianhao Zhang, Tingting Zhou, Sheng Liu, Wentao Li, Dong Zhang, Qinyu School of Electronics and Information Engineering Shenzhen518055 China Guangdong Provincial Key Laboratory of Space-Aerial Networking and Intelligent Sensing 518055 China Pengcheng Laboratory Shenzhen150001 China Tsinghua University Department of Electronic Engineering Beijing100084 China Macau University of Science and Technology School of Computer Science and Engineering 999078 China

In wireless sensors networks, integrating localization and communication technique is crucial for efficient spectrum and hardware utilizations. In this article, we present a novel framework of the unmanned aerial vehicle (UAV)-aided localization and communication for ground node (GN), where the average spectral efficiency (SE) is used to reveal the intricate relationship among the frame structure, channel estimation error, and localization accuracy. In particular, we first derive the lower bounds for channel estimation error and the 3-D location prediction error, respectively. Leveraging these comprehensive analysis, we formulate a problem to maximize the average SE in the UAV-GN communication, where the frame structure, beamwidth, and power allocation can be jointly optimized. Subsequently, we propose an efficient iterative algorithm to address this nonconvex problem with closed-form expressions for beamwidth design and power allocation. Numerical results demonstrate that the performance of our proposed method can approach the upper bound with low complexity, and achieve over 70% performance gain compared with communication-only benchmarks. In addition, the analysis highlights the dominated impacts of the Doppler effect on the average SE. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Model Predictive and Inversive control for State Transition of Dynamics Systems

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Advances in Astronautics science and technology 2022年第2期5卷 135-140页

作者： Tan, Tianle Chen, Jie Shanghai Aerospace Control Technology Institute Shanghai 201109 China Shanghai Key Laboratory of Space Intelligent Control Technology Shanghai 201109 China Shanghai Academy of Spaceflight Technology Shanghai 201109 China

In this paper, a new method of state stability, transition and tracking control for dynamics system based on model prediction and inversion is introduced. The estimation of system state bias in the future is obtained by model prediction. According to the dynamics evolution law of the controlled object, the control command to eliminate the future deviation is obtained by dynamics inversion. The compensation control is designed for the current and historical state deviations, and a state control method based on dynamics model of the controlled object is constructed. This method can be widely applied to various forms of control, and can better realize the state transition, tracking and stability control of dynamics system under the time constraint. The controller can be self-organized according to the model of the controlled object, and the parameters of the controller can be adjusted adaptively. It has good robustness to load/disturbance and deviations of model parameter, state measurement and control execution. The characteristics of this method are discussed, a simulation of rocket attitude control is given and the future research focus of this method is prospected. © 2021, Chinese Society of Astronautics.

关键词： Adaptive controllability Dynamics system Model prediction and inversion control Reachability Self-organization State transition Strong robust

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Particle Swarm Optimization based Trajectory Propagation for RLV Approach and Landing Phase

Particle Swarm Optimization based Trajectory Propagation for...

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2022 Chinese Automation Congress, CAC 2022

作者： Yan, Han Shen, Xiaxin Wang, Xinghu Beijing Institute of Control Engineering Beijing100094 China Science and Technology on Space Intelligent Control Laboratory Beijing100094 China Beijing Sun Wise Space Technology Ltd. Beijing100094 China University of Science & Technology of China Department of Automation Hefei230027 China

ISBN: (纸本)9781665465335

The trajectory propagation is used to estimate the flight states of the RLV when landing with a designed trajectory, so as to verify that whether the trajectory is suitable or not. Most of existing results are developed based on Euler numerical integration technique, and due to the implementation of the method, the efficiency of propagation may be low if a small integration step is used for high accuracy. To handle such issue, the paper propose a particle swarm optimization (PSO) based trajectory propagation method. With the proposed method, the efficiency of propagation can be significantly improved without losing accuracy. Simulations are done to show the advantages of our method. © 2022 IEEE.

关键词： Trajectories

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Experimental research on GM-APD LIDAR point cloud classification algorithm based on deep learning

Experimental research on GM-APD LIDAR point cloud classifica...

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2022 Applied Optics and Photonics China: Advanced Laser technology and Applications, AOPC 2022

作者： Jiang, Yanze Sun, Jianfeng Ding, Yuanxue Jiang, Peng Zhang, Hailong Li, Sining Zhou, Shuaijun National Key Laboratory of Science and Technology on Tunable Laser Institute of OptoElectronic Harbin Institute of Technology Heilongjiang Harbin150001 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (纸本)9781510662223

Geiger mode Avalanche Photo Diode (Gm-APD) array lidar is a lidar that can perform single-photon detection. It offers a wide range of applications due to its low power consumption, small size, and extended detecting distance. There haven't been many research on this detector's target classification because of its late development and small detector array. The classification technique based on the Gm-APD array lidar point cloud is the focus of this paper's research: Firstly, the Gm-APD array lidar is utilized to perform imaging tests on four targets from various angles in order to create a target classification *** that, several data preprocessing methods were chosen and implemented based on the characteristics of the obtained data, such as filling in missing values, performing range image and intensity image interpolation, using the principle of keyhole imaging to convert the range image to point cloud data, realizing the information fusion of distance image and intensity image, and using multiple point cloud data enhancement methods. Finally, the point cloud classification networks PointNet and PointNet++ are trained on point cloud data with varying levels of preprocessing, the results are compared and analyzed, and the impact of different preprocessing methods on the classification accuracy of the two networks is determined. Inferences were made and experiments were carried out to verify the inferences. The data set preprocessing method with the highest classification accuracy of the two networks is discovered, laying the groundwork for future Gm-APD lidar target classification and detection research. © 2023 SPIE.

关键词： Optical radar

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Improved Variable Deviation Collaborative control of Vector Nozzles for Aircraft Engine 43

Improved Variable Deviation Collaborative Control of Vector ...

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43rd Chinese control Conference, CCC 2024

作者： Dai, Jiacheng Ma, Yanhua Du, Xian Gao, Yongfeng Dalian University of Technology School of Control Science and Engineering Dalian116024 China Dalian University of Technology School of Integrated Circuits Dalian116024 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian116024 China

ISBN: (纸本)9789887581581

Vector nozzle is an adjustable tail nozzle in aircraft engines. Due to the complex structure and coupling effect of each actuator, the traditional collaborative control methods can hardly achieve the required time synchronization. In this paper, an improved variable deviation collaborative control method is proposed to address such issues, which promotes the synchronization performance of nozzle actuators through an improved deviation coupler. At the same time, an adaptive disturbance rejection controller is used to enhance the robustness of the system. The experimental results show that the error of synchronization time of each actuator in the vector nozzle is less than 5%, and the steady-state error of displacement is less than 1%, which meets the requirement of practical engineering. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Disturbance rejection

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Design of Cooperative Combat Task Architecture for Unknown Wide Area Cluster Reconnaissance and Strike

Design of Cooperative Combat Task Architecture for Unknown W...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Bu, Yunong Chi, Qingxi Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811581540

In the face of the requirements of information warfare in the future battlefield under the condition of high-intensity confrontation, cluster warfare has become the main trend of the development of some weapons and equipment. This makes us need to explore the cooperative operation mechanism of weapon equipment cluster, realize the rapid response of the cluster to the change of battlefield situation under the uncertain operation environment, complete the OODA cycle of operation, and improve the autonomous operation ability of the cluster. This paper takes the unknown wide area multi-target cooperative reconnaissance and strike task as the operational scenario, combs the task flow, function composition, network structure and data interaction relationship. Based on the task constraint, the architecture of cluster cooperative combat task is designed. The cooperative OODA closed-loop is preliminarily realized. It provides the basis for further exploring the overall technology of cooperative combat mission architecture. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Network architecture

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An Estimation Algorithm of Population Feature Distribution for the Imaging Constellation Task Planning Problem

An Estimation Algorithm of Population Feature Distribution f...

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Chinese control Conference (CCC)

作者： Yinan Ding Yongjun Lei Shuyi Wang Beijing Institute of Control Engineering Beijing China Science and Technology on Space Intelligent Control Laboratory Beijing China

An estimation algorithm of population feature distribution (EPFD) is proposed to improve the completion and imaging quality of imaging constellation observation tasks. Firstly, the observation task constraints and on-board resource constraints of agile imaging satellites are analyzed, the objective function of evaluating task completion and imaging quality is constructed, and the task planning model of agile imaging constellation is established. Then, the coding and decoding strategy with imaging time as the optimization object is designed. The concepts of global heuristic information and local heuristic information are given. A method for establishing the probability distribution model of imaging time based on heuristic information and a population evolution method are proposed. The directional search of imaging time is realized, and the completion of observation tasks and imaging quality are improved. Finally, the algorithm and particle swarm optimization algorithm are compared and analyzed through engineering examples. The results show that the algorithm has a fast convergence speed and a good optimization effect.

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