Robust Predictive Control Of Nonplanar Fully-Actuated Uavs,
2024
School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China
Robust Predictive Control Of Nonplanar Fully-Actuated Uavs, Yun Ma, Yuan Wang, Meng Li, Peng Wang, Yanling Tang
Journal of System Simulation
Abstract: Targeting the problem that nonplanar fully-actuated unmanned aerial vehicles (UAVs) are susceptible to external winds and unmodeled dynamics, the predictive control system with good robustness is designed. A nonlinear motion model with six degrees of freedom is established through the Newton-Euler approach. A linear extended state observer is designed to estimate the state variables by transforming the system affected by matched and unmatched disturbances into an equivalent system only affected by the matched disturbances. A predictive controller is designed for the equivalent system to reduce the output oscillation and input surging and a disturbance compensator is also designed to …
Reconnaissance Mission Planning Method For Air-Ground Heterogeneous Unmanned Systems,
2024
Department of Information and Communication, Academy of Army Armored Force, Beijing 100072, China
Reconnaissance Mission Planning Method For Air-Ground Heterogeneous Unmanned Systems, Guohui Zhang, Ya'nan Zhang, Ang Gao, Aoyu Xu
Journal of System Simulation
Abstract: Compared with the air-based homogeneous unmanned system, the motion capabilities, resource payloads, and combat scenes in the air-ground heterogeneous unmanned system increase the number of constraint conditions and significantly increase the computational complexity of the solution model. The modeling of collaborative combat missions and the efficient solution of large-scale problems are the key issues. With the time, path cost, and reconnaissance benefit as the objective functions, considering the constraints such as the endurance of unmanned platforms, a multi-objective programming model for the reconnaissance missions of an air-ground heterogeneous unmanned system is constructed. Aiming at the urban combat environments with …
A Simplification Method Of Large-Scale Unit Commitment Model Based On Boundary Method,
2024
China Electric Power Research Institute, Beijing 100192, China
A Simplification Method Of Large-Scale Unit Commitment Model Based On Boundary Method, Yanping Xu, Mingxin Zhao, Xiaohui Qin, Keyou He, Xiaohan Wu, Pei Zhang
Journal of System Simulation
Abstract: As the scale of power grid expands, in the market environment, the variables and constraints in the security-constrained unit commitment (SCUC) model considering power grid security constraints increase significantly and the solvability of the model reduces. When the model scale is too large, even the existing commercial solvers cannot solve it. Aiming at the model rapid solving, from the perspective of reducing the number of model constraints, a linear constraint simplification method based on the boundary method is proposed. The proposed method can effectively reduce the model's size by eliminating the redundant linear constraints. The IEEE-39, WECC 179 and …
Optimal Scheduling Strategy Of Virtual Power Plant With Carbon Emission And Carbon Penalty Considering Uncertainty Of Wind Power And Photovoltaic Power,
2024
College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Optimal Scheduling Strategy Of Virtual Power Plant With Carbon Emission And Carbon Penalty Considering Uncertainty Of Wind Power And Photovoltaic Power, Jijun Shui, Daogang Peng, Yankan Song, Qiang Zhou
Journal of System Simulation
Abstract: To better meet the development needs of China's new power system, an optimal scheduling strategy of virtual power plant(VPP) with carbon emission and carbon penalty considering the uncertainty of wind power and photovoltaic power is proposed. The mathematical description of photovoltaic(PV), wind turbine(WT), combined heat and power(CHP) unit and energy storage system (ESS) is carried out, and a wind-solar output model considering the uncertainty is established. The scenario generation and reduction method is used to generate the typical scenario. To maximize the overall operation benefit of VPP, considering carbon emission cost and carbon penalty, an optimal scheduling model of …
Flipper Control Method For Tracked Robot Based On Deep Reinforcement Learning,
2024
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Flipper Control Method For Tracked Robot Based On Deep Reinforcement Learning, Hainan Pan, Bailiang Chen, Kaihong Huang, Junkai Ren, Chuang Cheng, Huimin Lu, Hui Zhang
Journal of System Simulation
Abstract: Tracked robots with flippers have certain terrain adaptation capabilities. To improve the intelligent operation level of robots in complex environments, it is significant to realize the flipper autonomously control. Combining the expert experience in obstacle crossing and optimization indicators, Markov decision process(MDP) modeling of the robot's flipper control problem is carried out and a simulation training environment based on physics simulation engine Pymunk is built. A deep reinforcement learning control algorithm based on dueling double DQN(D3QN) network is proposed for controlling the flippers. With terrain information and robot state as the input and the four flippers' angle as the …
Short-Term Bus Passenger Flow Prediction Based On Convolutional Long-Short-Term Memory Network,
2024
School of Information Technology and Engineering, Tianjin University of Technology and Education, Tianjin 300222, China
Short-Term Bus Passenger Flow Prediction Based On Convolutional Long-Short-Term Memory Network, Jing Chen, Zhaochong Zhang, Linkai Wang, Mai An, Wei Wang
Journal of System Simulation
Abstract: To address the problem that the traditional short-time passenger flow prediction method does not consider the temporal characteristics similarity between the inter-temporal passenger flows, a shorttime passenger flow prediction model k-CNN-LSTM is proposed by combining the improved k-means clustering algorithm with the CNN and the LSTM. The k-means is used to cluster the intertemporal timeseries data, the k-value is determined by using the gap-statistic, and a traffic flow matrix model is constructed. A CNN-LSTM network is used to process the short-time passenger flows with spatial and temporal characteristics. The model is tested and parameter tuned by the real dataset. …
Ground Target Recognition And Damage Assessment Of Patrol Missiles Based On Multi-Source Information Fusion,
2024
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Ground Target Recognition And Damage Assessment Of Patrol Missiles Based On Multi-Source Information Fusion, Yibo Xu, Qinghua Yu, Yanjuan Wang, Ce Guo, Shiru Feng, Huimin Lu
Journal of System Simulation
Abstract: For the multiple patrol missiles to attack the high defense capacity targets, a mobile ground target detection and damage assessment method based on multi-source information fusion is proposed. The multi-source information fusion of infrared images and RGB images is carried out by using IoU determination. A novel two-stage tightly coupled damage assessment method based on YOLO-VGGNet of patrol missiles to mobile ground targets is proposed. This method can fully use the advantage of deep semantic information extraction of CNNs and introduce the infrared damaging information simultaneously to achieve the online and real-time damage assessment of mobile ground targets. The …
Research Advances On Electric Vehicle Routing Problem Models And Algorithms,
2024
School of Sciences, Jiangxi University of Science and Technology, Ganzhou 341000, China; School of Information Science and Engineering, Jiaxing University, Jiaxing 314001, China
Research Advances On Electric Vehicle Routing Problem Models And Algorithms, Helin Zhuang, Xiaoyun Xia, Kangshun Li, Zefeng Chen, Xianchao Zhang
Journal of System Simulation
Abstract: The development of electric vehicle provides an alternative to conventional fuel vehicles for logistics companies. Using electric vehicles has the merits of less pollution and low noise, but the characteristics of limited cruising range and limited number of charging stations are new challenges. Electric vehicle routing problems(EVRPs) have been widely used in transportation, logistics and other fields, and have received much attention. A comprehensive survey of EVRP and its many variants are presented and the respective backgrounds and applicable conditions are analyzed. The solving approaches of EVRPs are categorized, the strengths and weaknesses of each algorithm are analyzed, and …
Optimal Dispatch Of Microgrid Clusters Considering Energy Storage Life And Communication Failures,
2024
Department of Automation, North China Electric Power University, Baoding 071003, China
Optimal Dispatch Of Microgrid Clusters Considering Energy Storage Life And Communication Failures, Jianfang Jiao, Anjie Wang, Guang Wang, Jiale Xie
Journal of System Simulation
Abstract: To ensure the economy and stability of microgrid operation, the power fluctuations of renewable energy source (RES) and the lifetime characteristics of battery energy storage system (BESS) should be considered. The influence of charging and discharging depth and rate on the lifetime of BESS is researched, a model of battery energy storage system for real-time optimal scheduling is established, and the alternating direction method of multipliers is adopted for the distributed optimal scheduling of microgrid clusters. The distributed optimization method does not require any global information and can protect the privacy of microgrid in the maximum extent. Simulation results …
Dynamic Spatio-Temporal Anomaly-Aware Correlation Filtering Object Tracking Algorithm,
2024
College of Software, Liaoning Technical University, Huludao 125105, China
Dynamic Spatio-Temporal Anomaly-Aware Correlation Filtering Object Tracking Algorithm, Yunfei Qiu, Xiangrui Bu, Boqiang Zhang
Journal of System Simulation
Abstract: In view of the fact that the background perception algorithm does not establish a relationship with the spatio-temporal domain characteristics of the target, and cannot accurately deal with the occlusion, deformation and other abnormal tracking, a object tracking algorithm which can adaptively perceive the spatio-temporal anomalies is proposed. In the training stage of correlation filter, the adaptive spatial regularization term is introduced to establish a relationship with the spatio-temporal characteristics of sample. The abnormal perception method is proposed according to the peak value of response map. Taking advantage of the different confidence of historical filter and the continuity of …
Fault Detection Based On Sliding Window And Multiblock Convolutional Autoencoders,
2024
School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China
Fault Detection Based On Sliding Window And Multiblock Convolutional Autoencoders, Jianpeng Mou, Weili Xiong
Journal of System Simulation
Abstract: In order to further improve the fault detection performance and fully mine the timing and hidden feature information, a fault detection method based on convolutional auto encoder is proposed. On the basis of modeling the original information set, the modeling of cumulative information and rate of change information is added to enhance the mining of implicit information; The three reconstructed information sets are sampled by sliding windows, and time series feature extraction and modeling are performed based on convolutional auto encoders. Bayesian fusion of the decision results of the convolutional auto encoder is performed to obtain the statistics, and …
Improved Multi-Objective Swarm Algorithm To Optimize Wash-Out Motion And Its Simulation Experiment,
2024
College of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China
Improved Multi-Objective Swarm Algorithm To Optimize Wash-Out Motion And Its Simulation Experiment, Hui Wang, Le Peng
Journal of System Simulation
Abstract: Addressing the issues such as signal loss, distraction, and bad wash-out effect caused by improper parameter selection in classic wash-out algorithms, an improved multi-objective artificial bee colony algorithm is proposed to optimize the filter parameters of the classical wash-out algorithm to improve the effect. For the problems in the initialization and local optimization of traditional swarm algorithm, Circle mapping and Pareto local optimization algorithm are introduced. The human perception error model, acceleration difference model, and displacement model are established, and the model function is used as the objective function, the parameters of the classical wash-out algorithm is optimized by …
Bus Traffic Strategy Based On Immune Theory In Network Environment,
2024
School of Physics and Electronic Information, Anhui Normal University, Wuhu 241002, China; Anhui Provincial Engineering Laboratory on Information Fusion and Control of Intelligent Robot (Anhui Normal University), Wuhu 241002, China
Bus Traffic Strategy Based On Immune Theory In Network Environment, Cao Li, Rui Zheng, Xiaolu Ma, Ziqiong Ding, Junyi Zhong, Sheng Zhang, Jingjing Qi
Journal of System Simulation
Abstract: In V2X network environment, the bus system can obtain dynamic global information and the bus traffic strategy is carried out based on the road scene between adjacent bus stops. The mathematical model of bus rapid traffic is constructed with the difference of green time ratio as the main parameter. A hybrid genetic operator is proposed on the basis of the combination of genetic algorithm and immune theory, the design of affinity, the selection of excellent antibodies. A bus traffic strategy based on immune theory is proposed on the basis of the improvement of adaptive crossover and mutation probability. The …
Research On Vehicle Detection Method Based On Improved Yolox-S,
2024
College of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China
Research On Vehicle Detection Method Based On Improved Yolox-S, Xiliu Zhang, Xiaoling Zhang, Minjun He
Journal of System Simulation
Abstract: A improved vehicle detection model based on multi-scale feature fusion of YOLOX network is proposed to solve the problem of missing and false detection of small vehicle targets. Ghost-cross stage partial(CSP) based on the depth separable convolution is designed to replace part of cross stage partial in network to speed up the speed of detection. The max pooling mode of model is improved to Softpool mode, and coordinate attention mechanism is introduced to enhance the feature expression of target to be detected and to optimize the problem of target missing detection. Focal Loss is selected as the confidence loss …
Design And Application Of Hardware-In-The-Loop Simulation System For Infrared Imaging Guide Missile Test And Evaluation,
2024
PLA 63871 Troops, Huayin 714200, China
Design And Application Of Hardware-In-The-Loop Simulation System For Infrared Imaging Guide Missile Test And Evaluation, Jianbin Dou, Xiaobing Wang, Hongjian Yang, Yulong Gao
Journal of System Simulation
Abstract: The characteristics of the army's conventional infrared imaging guide missile hardware-in-theloop simulation system used for test and evaluation is analyzed, and a system that can meet the test and evaluation requirement of infrared imaging guide missile is designed. The key technologies such as universal system design, rapid iterative development design of heterogeneous communication data, high radiation infrared interference dual channel coupling simulation, high-precision timing and synchronization, generation of complex battlefield environment are solved. The application of the system is verified on the typical anti-tank missile and helicopter borne missile tests. The system can be used for infrared imaging guide …
Design Of 3d Visualization Monitoring System For Oil Field Pumping Unit Based On Unity3d,
2024
School of Mechanical Engineering, Xinjiang University, Urumqi 830017, China
Design Of 3d Visualization Monitoring System For Oil Field Pumping Unit Based On Unity3d, Liqiang Liu, Wenlei Sun, Yi Wang, Bingkai Wang
Journal of System Simulation
Abstract: Aiming at the defects of single monitoring form, low degree of 3D visualization and poor linkage of pumping unit, the information-physical real-time mapping is introduced to develop the 3D visualization monitoring system for oil field pumping unit. The digital space of pumping unit are designed and the design architecture of virtual-real interaction layer is built. The composition and relation framework of 3D visualization system are built. Combined with the inverse kinematics, the mathematical model is built, and the overall architecture of the pumping unit 3D visualization system is designed based on the five-dimensional model and Unity3D platform. The beam …
Using Natural Language Processing To Identify Mental Health Indicators In Aviation Voluntary Safety Reports,
2024
Fort Hill Group
Using Natural Language Processing To Identify Mental Health Indicators In Aviation Voluntary Safety Reports, Michael Sawyer, Katherine Berry, Amelia Kinsella, R Jordan Hinson, Edward Bynum
National Training Aircraft Symposium (NTAS)
Voluntary Safety Reporting Programs (VSRPs) are a critical tool in the aviation industry for monitoring safety issues observed by the frontline workforce. While VSRPs primarily focus on operational safety, report narratives often describe factors such as fatigue, workload, culture, staffing, and health, directly or indirectly impacting mental health. These reports can provide individual and organizational insights into aviation personnel's physical and psychological well-being. This poster introduces the AVIation Analytic Neural network for Safety events (AVIAN-S) model as a potential tool to extract and monitor these insights. AVIAN-S is a novel machine-learning model that leverages natural language processing (NLP) to analyze …
Sustainability Considerations Of Generative A.I.,
2024
West Chester University of Pennsylvania
Sustainability Considerations Of Generative A.I., Thomas Pantazes
Sustainability Research & Practice Seminar Presentations
Dr. Thomas Pantazes of the WCU Teaching and Learning Center shares Sustainability Considerations of Generative A.I.
Adopting Ai In Faculty Teaching Methodologies,
2024
Lynn University
Adopting Ai In Faculty Teaching Methodologies, Karima Lanfranco, Kristen Migliano, Ellen Ramsey, David G. Wolf
Faculty and Staff Publications & Presentations
No abstract provided.
Chatgpt Can Offer Satisfactory Responses To Common Patient Questions Regarding Elbow Ulnar Collateral Ligament Reconstruction,
2024
Thomas Jefferson University
Chatgpt Can Offer Satisfactory Responses To Common Patient Questions Regarding Elbow Ulnar Collateral Ligament Reconstruction, William Johns, Alec Kellish, Dominic Farronato, Michael G. Ciccotti, Sommer Hammoud
Rothman Institute Papers
PURPOSE: To determine whether ChatGPT effectively responds to 10 commonly asked questions concerning ulnar collateral ligament (UCL) reconstruction.
METHODS: A comprehensive list of 90 UCL reconstruction questions was initially created, with a final set of 10 "most commonly asked" questions ultimately selected. Questions were presented to ChatGPT and its response was documented. Responses were evaluated independently by 3 authors using an evidence-based methodology, resulting in a grading system categorized as follows: (1) excellent response not requiring clarification; (2) satisfactory requiring minimal clarification; (3) satisfactory requiring moderate clarification; and (4) unsatisfactory requiring substantial clarification.
RESULTS: Six of 10 ten responses were …
