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2023 International Conference on Ubiquitous communication, Ucom 2023

作者： Wang, Chenxi Qian, Li Ping Zhu, Huijie College of Information Engineering Zhejiang University of Technology Hangzhou China The 36th Research Institute of China Electronics Technology Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9798350340433

OTFS technology is attracting much attention due to its strong adaptability to high-speed mobility and high spectrum efficiency. Studies show that applying deep learning (DL) to traditional communication systems significantly improves their performance. To this end, this paper proposes an AI-Aid OTFS receiver to enhance the performance of OTFS systems in high-speed mobile communication scenarios. The proposed receiver employs two networks-a channel estimation network called TFNet and a decoding network called RecovNet. In the channel estimation module, TFNet performs more accurate channel estimation based on the results of traditional channel estimation methods. In the decoding module, RecovNet decodes the signal based on the equalized signals. To validate the superiority of our proposed receiver, we conduct comparative testing with a traditional receiver under the integer Doppler channel. The experimental results demonstrate that integrating DL technology in OTFS systems effectively enhances their performance. © 2023 IEEE.

关键词： Decoding

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A Novel Evaluation Strategy to Artificial Neural Network Model Based on Bionics

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Journal of Bionic engineering 2022年第1期19卷 224-239页

作者： Sen Tian Jin Zhang Xuanyu Shu Lingyu Chen Xin Niu You Wang School of Mathematics and Statistics Hunan Normal UniversityChangsha410081China College of Information Science and Engineering Hunan Normal UniversityChangsha410081China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China Key Laboratory of Industrial Control Technology Zhejiang UniversityHangzhou310058China Science and Technology on Parallel and Distributed Laboratory College of ComputerNational University of Defense TechnologyChangsha410199China Key Laboratory of Industrial Control Technology Institute of Cyber Systems and ControlZhejiang UniversityHangzhou310027China

With the continuous deepening of Artificial Neural Network(ANN)research,ANN model structure and function are improving towards diversification and ***,the model is more evaluated from the pros and cons of the problem-solving results and the lack of evaluation from the biomimetic aspect of imitating neural networks is not inclusive ***,a new ANN models evaluation strategy is proposed from the perspective of bionics in response to this problem in the ***,four classical neural network models are illustrated:Back Propagation(BP)network,Deep Belief Network(DBN),LeNet5 network,and olfactory bionic model(KIII model),and the neuron transmission mode and equation,network structure,and weight updating principle of the models are analyzed *** analysis results show that the KIII model comes closer to the actual biological nervous system compared with other models,and the LeNet5 network simulates the nervous system in ***,evaluation indexes of ANN are constructed from the perspective of bionics in this paper:small-world,synchronous,and chaotic ***,the network model is quantitatively analyzed by evaluation indexes from the perspective of *** experimental results show that the DBN network,LeNet5 network,and BP network have synchronous *** the DBN network and LeNet5 network have certain chaotic characteristics,but there is still a certain distance between the three classical neural networks and actual biological neural *** KIII model has certain small-world characteristics in structure,and its network also exhibits synchronization characteristics and chaotic *** with the DBN network,LeNet5 network,and the BP network,the KIII model is closer to the real biological neural network.

关键词： Artificial neural network(ANN) Back Propagation(BP)network Deep Belief Network(DBN) LeNet5 network Olfactory bionic model(KIII model) Small world Chaos Synchronous

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Acceleration of Formation control Based on Hessian Matrix of Artificial Potential Field 42

Acceleration of Formation Control Based on Hessian Matrix of...

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42nd Chinese control Conference, CCC 2023

作者： Han, Haoran Xi, Zhilong Lv, Maolong Cheng, Jian School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China Air Traffic Control and Navigation College Air Force Engineering University Xian710051 China

ISBN: (纸本)9789887581543

The formation control of multi-agent system has become a hotspot in recent years. One of the most commonly used methods is to use artificial potential field (APF) to generate the attractive and repulsive force to organize the agents into a low-energy and stable formation. In this paper, we regard the APF as the difference in the desired position, and introduce the derivative of the gradient of the APF with respect to time, which is simplified as the Hessian matrix of the APF, into the formation control from the perspective of trajectory tracking. The energy-based Lyapunov function is selected to prove the stability and collision avoidance ability of the proposed control law. Moreover, we show that the maneuverability of the multi-agent system is enormously improved with the additional Hessian matrix term. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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Collision-Free Formation control of Multi-agent System with Low Oscillation 7th

Collision-Free Formation Control of Multi-agent System with ...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Li, Jingyi Han, Haoran Lv, Maolong Sun, Chenyang Cheng, Jian Glassgow School University of Electronic Science and Technology of China Chengdu611731 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China Air Traffic Control and Navigation College Air Force Engineering University Xian710051 China

ISBN: (纸本)9789819733279

In recent years, multi-agent systems are becoming more complex, scalable, adaptive, and integrating machine learning for enhanced capabilities. A popular approach for addressing this challenge involves the utilisation of artificial potential functions (APF). In this article, we address the problem of obstacle avoidance and achieving a predefined formation, particularly promoting smooth trajectory generation in multi-agent formation control. We employ the APF method to enhance the smoothness of the agents’ movement paths during these tasks. Collision damping terms are generated by differentiating the gradient of APF with respect to time. Incorporating generated damping terms in the APF control, we suppress irregular fluctuations during agents’ motion procedures. To ensure stability in the multi-agent system, we design an energy-based Lyapunov function and utilise it for proof. Simulation examples are presented to validate the theoretical results and demonstrate the advantages of the proposed control algorithm. Through these simulations, it becomes evident that the collision-free formation control algorithm enhances the smoothness of the agents’ trajectories. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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Performance Analysis of A Missile Guidance and control System Model for Precise Target Tracking 3

Performance Analysis of A Missile Guidance and Control Syste...

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3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024

作者： Bhattacharjee, Rituraj Mukherjee, Subhradip Manipal Institute of Technology Manipal Academy of Higher Education Department of Instrumentation & Control Engineerig Udupi-Karkala Road Karnataka Manipal576104 India Mvj College of Engineering Electronics and Communication Department Bangalore India

ISBN: (纸本)9798350384598

A missile navigation system model is developed and analyzed in this work. The flight command structure is a crucial component which improves the efficiency of the system. It has a major impact on both the accuracy of the strike and precise control over the missile's performance. The goal of the flight command structure is to instruct the missile to follow the steering directive produced by the control system. The system's representation is determined by how well it establishes the flying course required to intercept the target and sends the commands to the attitude control system required to keep the missile on course while taking the airframe's dynamics and relevant aerodynamic characteristics into account. The missile is guided to attack the target after it has been tracked, and its trajectory is determined by the homing guidance loop utilizing the PID controller-based autopilot mode. In the MATLAB simulation environment, dynamic performance of the missile guidance system is simulated using a step response technique based on time. © 2024 IEEE.

关键词： MATLAB

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Intelligent Agricultural Drones Utilizing Nano-Fertilizer Dispensation for Precision Farming

Intelligent Agricultural Drones Utilizing Nano-Fertilizer Di...

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International Conference on communication, Computing and Internet of Things (IC3IoT)

作者： G Jayanthi W Nancy B. Umamaheswari R Chithrakkannan R Sujith S Sathya Prasanna Department of Instrumentation and control Engineering Sri Sairam Engineering college Department of Electronics and Communication Engineering Jeppiaar Institute of Technology Department of Electronics and Communication Engineering Sri Sairam Engineering college

ISBN: (数字)9798350352689

ISBN: (纸本)9798350352696

An innovative approach to precision agriculture through the integration of artificial intelligence (AI) and nano-fertilizer technology in an agricultural drone system. The proposed system aims to optimize crop yield, reduce environmental impact, and enhance resource efficiency by employing advanced AI algorithms for crop health assessment and nano-fertilizers for targeted nutrient delivery. The drone's real-time decision-making capabilities, coupled with precise dispensation of nano-sized fertilizers, contribute to sustainable farming practices. Field trials demonstrate promising results in terms of improved crop productivity, resource utilization, and minimized environmental footprint.

关键词： Productivity Soil Real-time systems Telecommunication computing Resource management Internet of Things Artificial intelligence

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Semi-asynchronous personalized federated learning for short-term photovoltaic power forecasting

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Digital communications and Networks 2023年第5期9卷 1221-1229页

作者： Weishan Zhang Xiao Chen Ke He Leiming Chen Liang Xu Xiao Wang Su Yang College of Computer Science and Technology China University of Petroleum(East China)China Sichuan Energy Internet Research Institute Tsinghua UniversityChina School of Computer and Communication Engineering Beijing University of Science and TechnologyChina State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Computer Science Fudan UniversityChina

Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient training data and enough computational ***,there are challenges in building models through centralized shared data due to data privacy concerns and industry *** learning is a new distributed machine learning approach which enables training models across edge devices while data reside *** this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM *** design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting *** evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.

关键词： Photovoltaic power forecasting Federated learning Edge computing CNN-LSTM

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Performance Analysis of Different controller Schemes of Interval Type-2 Fuzzy Logic in controlling of Mean Arterial Pressure During Infusion of Sodium Nitroprusside in Patients

Performance Analysis of Different Controller Schemes of Inte...

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Congress on control, Robotics, and Mechatronics, CRM 2023

作者： Mallick, Ayushi Yadav, Jyoti Chhabra, Himanshu Agarwal, Shivangi Department of Instrumentation and Control Engineering NSUT Sector-3 Delhi India Department of Electrical and Communication Engineering M. L. V. Textile and Engineering College Rajasthan Bhilwara India Department of Electronics Engineering Ramrao Adik Institute of Technology Nerul Navi Mumbai India

ISBN: (纸本)9789819955206

This research work is on designing an optimum and robust controller to improve the infusion of drug in patients during post-operative conditions in order to automatically control the mean arterial pressure. The control of mean arterial pressure of critically-ill patients is a prominent research field due to its ability to lessen recovery time, lower medical costs, and better medical staff management by lowering their burden. However, due to uncertainty in patient’s sensitivity toward the drug infused and external disturbance/noise, this is a complicated task. In this work, two efficient controller schemes, interval type-2-fuzzy logic controller-proportional integral derivative and fractional order-interval type-2-fuzzy logic controller-proportional derivative + proportional integral controller are presented. For effective optimization of these control schemes, one of the most effective nature inspired optimization, cuckoo search algorithm is implemented for finding their optimal values of parameters. In the work, simulation results and performance index i.e., settling time, overshoot IAE values shows superior performance of fractional order-interval type-2-fuzzy logic controller-proportional derivative + proportional integral controller over IT2-FLC-PID controller. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Three term control systems

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Intelligent vehicle path tracking based on feedback linearization and LQR under extreme conditions 41

Intelligent vehicle path tracking based on feedback lineariz...

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第41届中国控制会议

作者： Yi Sun Qikun Dai Jun Liu Xu Zhao Hongyan Guo College of Communication Engineering Jilin University The State Key Laboratory of Automotive Simulation and Control Jilin University The Department of Aviation Electrical Engineering Jilin Institute of Chemical Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

It proposes a path following control strategy for intelligent vehicles under extreme conditions based on feedback linearization and linear quadratic regulator(LQR).Firstly,the vehicle dynamics model and the vehicle kinematics model are established,and the affine nonlinear vehicle system model under the extreme condition is established by these two ***,the complex nonlinear vehicle system model is linearized using the feedback linearization method to obtain a simpler linear system ***,according to the obtained linear vehicle system model,the LQR method is used to design the tracking controller to obtain the optimal control input,so as to ensure the stability of the system and the optimality of the target,and realize the intelligent vehicle path *** affirm the effectiveness of the tracking method,a series of Carsim/Simulink co-simulation experiments are carried *** results show that the effects of path tracking combined with feedback linearization and LQR are significantly better than the other two methods,thus the path tracking method proposed in the paper is effectively verified.

关键词： Feedback Linearization LQR Affine Nonlinear Vehicle System Model Extreme conditions Path Tracking

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A Latency-offset Online Trajectory Planner based on Successive Convex Approximation

A Latency-offset Online Trajectory Planner based on Successi...

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2022 IEEE International Conference on Unmanned Systems, ICUS 2022

作者： Li, Yiming Jiang, Bin Yang, Junan Wang, Jian Li, Beibei Huang, Keju Shao, Kun College of Electronic Engineering National University of Defense Technology Hefei China Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

An online trajectory planner permits autonomous unmanned vehicles to maneuver in a changing mission scenario and varying environment. However, in real-time online plannings, task performance, completeness and accuracy is seriously challenged by the latency during mission planning and scheme computation. To address the issue, we propose a latency-correcting online trajectory planner based on successive convex approximation (SCA), which is aiming at offset the latency in the planning. In this work, two types of latency are considered, i.e., a prior known variable and computation, where the latter one poses a problem. With this, we devise an online latency method to predict computing latency by conducting time complexity analysis. The experiment is to design an optimal UAV trajectory to serve the eavesdropping of an uncooperative emitter. The results showed this harmful latency effect, and then demonstrated the improved accuracy and task performance of the proposed planner. © 2022 IEEE.

关键词： Trajectories

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