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2020 International Conference on Mechatronics technology and intelligent Manufacturing, ICMTIM 2020

作者： Xie, Ruidong Yang, Haichuan Yi, Yingmin Key Lab of Manufacturing Equipment of Shaanxi Province Xi'an University of Technology Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

Aiming at the effect of selective laser sintering technology used in 3D printing, the recursive least squares method was applied to fitting a control system model for quantification the relationship between laser power and corresponding temperature in this paper. The internal model control method is considered based on the establishing model. The controller is put into the actual 3D printing power control system for controlling the laser power. In the experiment, both internal model controller and the PID controller for the 3D printer are researched and deployed for comparing the their effects in the paper. The experimental result illustrates that the IMC based on the recursive least squares method is of effectiveness. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： 3D printers

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Mixed Motivation Driven Social Multi-Agent Reinforcement Learning for Autonomous Driving

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IEEE/CAA Journal of Automatica Sinica 2025年第6期12卷 1272-1282页

作者： Long Chen Peng Deng Lingxi Li Xuemin Hu State Key Laboratory of Multimodal Artificial Intelligence Systems and the State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing WAYTOUS Inc. Beijing Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China School of Computer Science and Information Engineering Hubei University Wuhan China Purdue School of Engineering and Technology Indiana University-Purdue University Indianapolis Indianapolis IN USA School of Artificial Intelligence Hubei University Wuhan Key Laboratory of Intelligent Sensing System and Security (Hubei University) Ministry of Education Wuhan China

Despite great achievement has been made in autonomous driving technologies, autonomous vehicles (AVs) still exhibit limitations in intelligence and lack social coordination, which is primarily attributed to their reliance on single-agent technologies, neglecting inter-AV interactions. Current research on multi-agent autonomous driving (MAAD) predominantly focuses on either distributed individual learning or centralized cooperative learning, ignoring the mixed-motive nature of MAAD systems, where each agent is not only self-interested in reaching its own destination but also needs to coordinate with other traffic participants to enhance efficiency and safety. Inspired by the mixed motivation of human driving behavior and their learning process, we propose a novel mixed motivation driven social multi-agent reinforcement learning method for autonomous driving. In our method, a multi-agent reinforcement learning (MARL) algorithm, called Social Learning Policy Optimization (SoLPO), which takes advantage of both the individual and social learning paradigms, is proposed to empower agents to rapidly acquire self-interested policies and effectively learn socially coordinated behavior. Based on the proposed SoLPO, we further develop a mixed-motive MARL method for autonomous driving combined with a social reward integration module that can model the mixed-motive nature of MAAD systems by integrating individual and neighbor rewards into a social learning objective for improved learning speed and effectiveness. Experiments conducted on the MetaDrive simulator show that our proposed method outperforms existing state-of-the-art MARL approaches in metrics including the success rate, safety, and efficiency. More-over, the AVs trained by our method form coordinated social norms and exhibit human-like driving behavior, demonstrating a high degree of social coordination.

关键词： Measurement Reinforcement learning Safety Driver behavior Autonomous vehicles Optimization

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Exploring the Economic Feasibility of Advanced Air Mobility in the Early Stages

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on intelligent Vehicles 2024年第5期9卷 4826-4830页

作者： Jingqiu Guo Long Chen Lingxi Li Xiaoxiang Na Ljubo Vlacic Fei-Yue Wang Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University–Purdue University Indianapolis (IUPUI) Indianapolis IN USA Department of Engineering University of Cambridge Cambridge U.K. Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith University Nathan QLD Australia State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Engineering Macau University of Science and Technology Macau China

Advanced Air Mobility (AAM) envisages a sustainable, safe, convenient, and affordable air transport system. In socio-technical transition of AAM, there are a number of trade-offs in ecosystem that need to be studied. Three perspectives on economic feasibility are explored: first, based on history of VTOL services and value of time estimates, we discuss whether AAM can provide customers with competitive mobility services; second, what are the stakeholders’ insights on the deployment of AAM; last, the experience in the development of autonomous driving technology, such as parallel intelligence, can inform future AAM research.

关键词： Active appearance model Costs Economics Transportation Helicopters Aircraft propulsion Public transportation

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Self-Organized Criticality in C. Elegans Neural Network

Self-Organized Criticality in C. Elegans Neural Network

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Chinese control Conference (CCC)

作者： Xiao Gu Jian Liu Ye Yuan Peng Zhao Kuankuan Xin Tao Fang Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Shanghai Engineering Research Centre of Intelligent Control and Management Shanghai China Institute of Machine Intelligence University of Shanghai for Science and Technology Shanghai China Queensland Brain Institute The University of Queensland Brisbane QLD Australia

The self-organized criticality is a fundamental property for organisms to perform normal functional activities. Extensive large-scale biological neural network researches have found the existence of self-organized criticality through avalanche phenomenon, which is typical characteristic of self-organized criticality. However, such research method is not suitable for small-scale biological neural network, because number of neurons in small-scale biological neural network is not large enough to support the emergence of avalanche phenomenon. It has been demonstrated that branching parameter can also be used to describe the propagation of activity in the neural network. Here, in this paper, the C. elegans neural network composed of 302 neurons is selected to investigate the existence of self-organized criticality using branching parameter. Based on the obtained connectome of C. elegans, a directed graph model is constructed to simulate the gradient potential of neurons and the activity of C. elegans, then, the existence of self-organized criticality in the neural network of C. elegans is proved by using branching parameter method. Meanwhile, the result is further confirmed by analyzing the calcium activity data of C. elegans obtained from biological experiments.

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Echo state network based symbol detection in chaotic baseband wireless communication

arXiv

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arXiv 2021年

作者： Yin, Hui-Ping Bai, Chao Ren, Hai-Peng The Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China The Xi’an Key Laboratory of Intelligent Equipment Xi’an Technological University Xi’an710021 China

In some Internet of Things (IoT) applications, multipath propagation is a main constraint of communication channel. Recently, the chaotic baseband wireless communication system (CBWCS) is promising to eliminate the inter-symbol interference (ISI) caused by multipath propagation. However, the current technique is only capable of removing the partial effect of ISI, due to only past decoded bits are available for the suboptimal decoding threshold calculation. However, the future transmitting bits also contribute to the threshold. The unavailable future information bits needed by the optimal decoding threshold are an obstacle to further improve the bit error rate (BER) performance. Different from the previous method using echo state network (ESN) to predict one future information bit, the proposed method in this paper predicts the optimal threshold directly using ESN. The proposed ESN-based threshold prediction method simplifies the symbol decoding operation by removing the threshold calculation from the transmitting symbols and channel information, which achieves better BER performance as compared to the previous method. The reason for this superior result lies in two folds, first, the proposed ESN is capable of using more future symbols information conveyed by the ESN input to get more accurate threshold;second, the proposed method here does not need to estimate the channel information using Least Square method, which avoids the extra error caused by inaccurate channel information estimation. By this way, the calculation complexity is decreased as compared to the previous method. Simulation results and experiment based on a wireless open-access research platform under a practical wireless channel, show the effectiveness and superiority of the proposed method. Copyright © 2021, The Authors. All rights reserved.

关键词： Bit error rate

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On the Approximation of the Quotient of Two Gaussian Densities for Multiple-Model Smoothing

On the Approximation of the Quotient of Two Gaussian Densiti...

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International Conference on Information Fusion

作者： Yi Liu Xi Li Le Yang Lyudmila Mihaylova Yanbo Xue Department of Electrical and Computer Engineering University of Canterbury Christchurch NZ State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems National University of Defense Technology Changsha China Department of Automatic Control and System Engineering University of Sheffield Sheffield UK Career Science Lab Beijing China

The quotient of two multivariate Gaussian densities can be written as an unnormalized Gaussian density, which has been applied in some recently developed multiple-model fixed-interval smoothing algorithms. However, this expression is invalid if instead of being positive definite, the covariance of the unnormalized Gaussian density is indefinite (i.e., it has both positive and negative eigenvalues) or undefined (i.e., computing it requires inverting a singular matrix). This paper considers approximating the quotient of two Gaussian densities in this case using two different approaches to mitigate the caused numerical problems. The first approach directly replaces the indefinite covariance of the unnormalized Gaussian density with a positive definite matrix nearest to it. The second approach computes the approximation through solving, using the natural gradient, an optimization problem with a Kullback-Leibler divergence-based cost function. This paper illustrates the application of the theoretical results by incorporating them into an existing smoothing method for jump Markov systems and utilizing the obtained smoothers to track a maneuvering target.

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Design and Performance Analysis of a Chaotic Pseudo Orthogonal Carriers Multi-Access Communication system

arXiv

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arXiv 2021年

作者： Bai, Chao Yao, Jun-Liang Sun, Yu-Zhe Ren, Hai-Peng Xi’an Key Laboratory of Intelligent Equipment Xi’an Technological University Xi’an710021 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

A Chaotic Pseudo Orthogonal Carriers Multi-Access (CPOCMA) communication based on Chaotic Pseudo Orthogonal Shape-forming Filter (CPOSF) bank, Chaotic Pseudo Orthogonal Matched Filter (CPOMF) bank and Chaotic Pseudo Orthogonal Correlation Filter (CPOCF) bank is proposed in this work. At the transmitter, the multiple CPOSFs are used to generate pseudo orthogonal signals. It provides a good trade-off between spectrum efficiency and high bit transmission rate. At the receiver, the CPOMF bank and CPOCF bank are used to maximize the Signal-to-Noise Ratio (SNR) and extract the received information from each sub-channel, respectively. The received signal is demodulated by averaging the sampled sequence from the matched filter bank output and sorting the sampling sequence from the CPOCF bank output to recover the transmitted information bits. The proposed CPOCMA communication system not only offers multiuser access with high reliability and high data transmission rate, but also achieves higher spectrum efficiency. Analytical Bit Error Rate (BER) expression is derived. The proposed communication system performance has been evaluated in Additive White Gaussian Noise (AWGN) channel and wireless channel by both numerical simulations and experiments based on a Wireless open-Access Research Platform (WARP), the results show the effectiveness and the superiority of the proposed method. Copyright © 2021, The Authors. All rights reserved.

关键词： Numerical methods

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Target tracking algorithm with adaptive learning rate complementary filtering

Target tracking algorithm with adaptive learning rate comple...

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第三十九届中国控制会议

作者： Yulei Pan Yongqiang Bai Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

The Correlation filtering algorithm is not effective for fast deformation and fast movement. It is easy to lose when encountering problems such as occlusion. However, it has a good advantage of dealing with situations such as motion blur and lighting changes. A tracking algorithm based on color statistical features has a good effect on the rotation and translation of *** Staple algorithm combines the two algorithms to track using complementary fusion, but it also does not handle the occlusion and other issues well. In this paper, based on the Staple algorithm, the average peak correlation energy（APCE） and the maximum response are introduced. The value is used as the tracking confidence, and a detector using a support vector machine（SVM） is *** the tracking confidence is low, the target is blocked or moved violently. At this time, the detector works,and the search area is expanded around the original area for the target. At the same time, because the traditional tracking algorithm uses a fixed learning rate to update the template, this paper uses an adaptive tracking learning rate. When the tracking confidence is low, the update speed of the target model is reduced, which can effectively deal with the occlusion deformation in the tracking process. OTB100 benchmark experiments show that this method can solve the occlusion problem during target tracking. The degree of change is robust and stability.

关键词： Target Tracking Complementary Filtering Re-detection Adaptive Learning Rate

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Influence of Si buffer layer on the crystal quality of SiGe films in Ge/Si/SiGe heterostructures: A molecular dynamics investigation

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Surface science 2025年 761卷

作者： Xie, Jianan Lin, Tao Wang, Cailin College of Automation and Information Engineering Xi'an University of Technology Xi'an710048 China Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

SiGe materials have become a research hotspot due to their important applications in semiconductor devices, especially in optoelectronic and high-speed electronic devices. In this study, based on molecular dynamics simulations, the influence of the Si buffer layer on the quality of films in Ge/Si/SiGe heterostructures is investigated. By simulating the growth process of the Ge/Si/SiGe heterostructure, a deposition model based on Ge(100) substrates is established. Inspired by the concept of reverse gradient buffer layers, Si buffer layers are directly grown on Ge substrates, followed by the deposition of SiGe films. This study primarily investigates the effects of the growth temperature and deposition thickness of the Si buffer layer on the quality of SiGe films. Based on the deposition parameters identified as suitable under the current simulation conditions (620 °C, 9.7 nm), the influence of the buffer layer on SiGe films with varying Ge compositions is further analyzed. The results show that the dislocations and stacking faults formed in the Si buffer layer effectively relieve the stress caused by lattice mismatch, thus improving the crystal quality of the subsequent SiGe films. This study provides theoretical insights into the Ge/Si/SiGe heterostructure film growth process, which helps enhance the quality of SiGe films and expands their applications in semiconductor devices. © 2025

关键词： Lattice mismatch

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Fully Decentralized DC Optimal Power Flow Model And Its Solution

Fully Decentralized DC Optimal Power Flow Model And Its Solu...

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China International Electrical and Energy Conference (CIEEC)

作者： Guangtao Hao Xueshan Han XueJun Chen Sibei Luo Shifeng Han Pingfeng Ye School of Mechanical Electrical & Information Engineering Putian University Putian China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China New Engineering and Industry College of Putian University Putian China Intelligent Manufacturing of Huzhou College Huzhou China School of Management of Putian University Putian China College of Energy Storage Technology of Shandong University of Science and Technology Qingdao China

In view of the fact that renewable energy power generations such as wind and solar energy have been integrated into the power system in a high proportion in a distributed manner, driven by factors such as privacy and security of various power supply stakeholders, the power supply of the power system presents a decentralized management and control situation, making the traditional centralized DC optimal power flow difficult to achieve. In this paper, a fully decentralized DC optimal power flow model, its solution method and application are proposed. Firstly, based on the economic dispatch model of the traditional consensus algorithm, the node phase decentralized calculation method is established and the active power flow decentralized calculation method of the transmission line is given to determine the system overload line. Secondly, the improved Lagrangian optimal model of the centralized DC optimal power flow is proposed and the optimization equations are derived. Thirdly, on this basis, combined with the improved traditional consensus algorithm, the fully distributed DC optimal power flow model and its solution method are realized. Finally, a real system is taken as an example to demonstrate the effectiveness of the proposed method.

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