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Articles 811 - 840 of 4244
Full-Text Articles in Artificial Intelligence and Robotics
Path Planning Of Mobile Robots Based On Memristor Reinforcement Learning In Dynamic Environment, Hailan Yang, Yongqiang Qi, Baolei Wu, Dan Rong
Path Planning Of Mobile Robots Based On Memristor Reinforcement Learning In Dynamic Environment, Hailan Yang, Yongqiang Qi, Baolei Wu, Dan Rong
Journal of System Simulation
Abstract: In order to solve the path planning problem of mobile robots in dynamic environment, two-layer path planning algorithm based on improved ant colony algorithm and MA-DQN algorithm is proposed. Static global path planning is accomplished by ant colony algorithm that improved the probabilistic transfer function and the pheromone updating principle; the traditional DQN algorithm structure is improved by using the memristor as the synaptic structure of neural network, and then completed the local dynamic obstacle avoidance of the mobile robot. The path planning mechanism is switched according to whether there are dynamic obstacles within the sensing range of the …
Attack Decision-Making Model Of Armed Helicopter Based On Multi-Index Fuzzy Set, Chunyan Wang, Xiang Wang, Minchi Kuang, Danfeng Wu, Zhengtong Li
Attack Decision-Making Model Of Armed Helicopter Based On Multi-Index Fuzzy Set, Chunyan Wang, Xiang Wang, Minchi Kuang, Danfeng Wu, Zhengtong Li
Journal of System Simulation
Abstract: Aiming at the attack decision-making task requirements of armed helicopters in uncertain battlefield environment, the constructed multi-index fuzzy set is quantitatively characterized by the improved Gaussian model. The strategic benefit value model is constructed by using the combat restraint relationship, and the target ranking set is obtained by dynamically assigning the weight factors of the threat value and the strategic benefit value to complete the attack decision-making. The results show that the proposed method can better use the threat index data in modeling, and can provide theoretical guidance and modeling reference to improve the decision-making advantage of armed …
Research On Period Emergency Supply Distribution Optimization Under Uncertainty, Li Zhang, Mingling He, Qiushuang Yin, Ning Li, Le'an Yu
Research On Period Emergency Supply Distribution Optimization Under Uncertainty, Li Zhang, Mingling He, Qiushuang Yin, Ning Li, Le'an Yu
Journal of System Simulation
Abstract: Aiming at the uncertainty and multi-periodicity of emergency supply distribution, a novel period vehicle routing problem(PVRP) multi-objective optimization model is built and a three-step optimization method is proposed. A triangular fuzzy number is used to eliminate the uncertainty. An AHP approach is used to transform the multi-objective function into the single objective function. An improved ACO algorithm is proposed to solve the single objective optimization problem. By classical data set, the time effectiveness of proposed method on emergency supply distribution problem is verified. The computational advantage in convergence speed is proved by the comparative analysis of the proposed …
Pedestrian Evacuation Model Considering Emotional Infection, Fan Dong, Qimiao Xie, Xiaolian Li, Shuchao Cao
Pedestrian Evacuation Model Considering Emotional Infection, Fan Dong, Qimiao Xie, Xiaolian Li, Shuchao Cao
Journal of System Simulation
Abstract: To explore the role of panic in crowd evacuation, a crowd evacuation model considering panic infection is constructed based on SIR model, SIS model and CA model. The influences of emotional threshold and emotional decay rate on the evacuation process of pedestrians are discussed. The results show that pedestrians under high panic might lose rational judgment and hinder the evacuation of the crowd around, resulting in a decrease of evacuation efficiency. It can be found that the state of an individual depends on the infection threshold and the immune threshold. The emotional decay rate affects the change rate of …
Improved Object Detection Of Yolov4 In Foggy Conditions, Shugang Liu, Linkun Zhang, Haodong Du, Hongtao Wang
Improved Object Detection Of Yolov4 In Foggy Conditions, Shugang Liu, Linkun Zhang, Haodong Du, Hongtao Wang
Journal of System Simulation
Abstract: Aiming at the low detection accuracy in foggy weather, a new defogging target detection method based on DeblurGANv2 and YOLOv4 is proposed. In the method, image enhancement algorithm DeblurGANv2 in the generation countermeasure network is added to the preprocessing module of YOLOv4 to preprocess the foggy image and retain the high-quality texture and color information of the image, lightweight neural network ShuffleNet V2 is used to replace the CSPDarkNet53 network used for backbone feature extraction in YOLOv4 to improve the speed of model mark detection. Attention mechanism is added to the feature extraction network of YOLOv4 to enhance the …
Obstacle Avoidance Path Planning And Simulation Of Mobile Picking Robot Based On Dppo, Junqiang Lin, Hongjun Wang, Xiangjun Zou, Po Zhang, Chengen Li, Yipeng Zhou, Shujie Yao
Obstacle Avoidance Path Planning And Simulation Of Mobile Picking Robot Based On Dppo, Junqiang Lin, Hongjun Wang, Xiangjun Zou, Po Zhang, Chengen Li, Yipeng Zhou, Shujie Yao
Journal of System Simulation
Abstract: Aiming at the autonomous decision-making difficulty of mobile picking robots in random and changeable complicated path environment during field operations, an autonomous obstacle avoidance path planning method based on deep reinforcement learning is propose. By setting the state space and action space and using the artificial potential field method to design the reward function, an obstacle penalty coefficient setting method based on collision cone collision avoidance detection is proposed to improve the autonomous collision avoidance ability. A virtual simulation system is constructed, in which the learning and training of the mobile picking robot is carried out and verified by …
Intelligent Path Planning For Mobile Robots Based On Sac Algorithm, Laiyi Yang, Jing Bi, Haitao Yuan
Intelligent Path Planning For Mobile Robots Based On Sac Algorithm, Laiyi Yang, Jing Bi, Haitao Yuan
Journal of System Simulation
Abstract: Aiming at the high dimension, slow convergence and complex modelling of traditional path planning algorithms for mobile robots, a new intelligent path planning algorithm is proposed, which is based on deep reinforcement learning soft actor-critic (SAC) algorithm to save the poor performance of robot in complicated environments with static and dynamic obstacles. An improved reward function is designed to enable mobile robots to quickly avoid obstacles and reach targets by using state dynamic normalization and priority experience pool techniques. To evaluate the performance, a pygame-based simulation environment is constructed. Compared with proximal policy optimization(PPO) algorithm, experimental …
Intelligent Air Defense Task Assignment Based On Assignment Strategy Optimization Algorithm, Jiayi Liu, Gang Wang, Qiang Fu, Xiangke Guo, Siyuan Wang
Intelligent Air Defense Task Assignment Based On Assignment Strategy Optimization Algorithm, Jiayi Liu, Gang Wang, Qiang Fu, Xiangke Guo, Siyuan Wang
Journal of System Simulation
Abstract: Aiming at the insufficient solving speed of assignment strategy optimization algorithm in largescale scenarios, deep reinforcement learning is combined with Markov decision process to carry out the intelligent large-scale air defense task assignment. According to the characteristics of large-scale air defense operations, Markov decision process is used to model the agent and a digital battlefield simulation environment is built. Air defense task assignment agent is designed and trained in digital battlefield simulation environment through proximal policy optimization algorithm. The feasibility and advantage of the method are verified by taking a large-scale ground-to-air countermeasure mission as an example.
Real-Time Simulation Method Of Ultra-High-Definition Video Texture, Yangyang Liu, Gangyi Ding, Dapeng Yan, Tong Xue
Real-Time Simulation Method Of Ultra-High-Definition Video Texture, Yangyang Liu, Gangyi Ding, Dapeng Yan, Tong Xue
Journal of System Simulation
Abstract: With the development and promotion of ultra-high-definition video technology, how to quickly simulate ultra-high-definition video texture has gradually become an important research issue. Aiming at the completeness and high efficiency of simulation, a real-time simulation method of ultra-high-definition video texture is proposed to improve the video texture quality and display frequency simultaneously. A fast generation method of video texture based on GPU parallel is designed, which solves the time-consuming problem of decoding and transcoding. An efficient data transmission method based on shared texture is proposed. On the basis of the simulation engine, the real-time simulation system of ultra-high-definition video …
Research On Nested Named Entity Recognition In Missile Field Text, Jingwen Guan, Xiao Song, Xiaoqing Li, Tong Yang, Junhua Zhou
Research On Nested Named Entity Recognition In Missile Field Text, Jingwen Guan, Xiao Song, Xiaoqing Li, Tong Yang, Junhua Zhou
Journal of System Simulation
Abstract: Compared with the text recognition in conventional fields, it is difficult to recognize the large number of nested named entities in professional terms. This is also one of the care challenges in building the knowledge graph in aerospace field. For the named entity recognition technologies, bidirectional long short-term memory network plus conditional random field (BiLSTM-CRF) is often used to identify entities, which is difficult to distinguish the complex relationships such as nesting and intersection of terms in missile field. In order to solve the problem, based on the nested entity labeling of domain text, a nested named entity recognition …
Robot Path Planning By Fusing Particle Swarm Algorithm And Improved Grey Wolf Algorithm, Menglong Cao, Wenbin Zhao, Zhiqiang Chen
Robot Path Planning By Fusing Particle Swarm Algorithm And Improved Grey Wolf Algorithm, Menglong Cao, Wenbin Zhao, Zhiqiang Chen
Journal of System Simulation
Abstract: Aiming at the long paths and slow convergence speed of GWO algorithm in robot path planning, a hybrid PSO-GWO algorithm based on PSO algorithm and the improved GWO algorithm is proposed. By running PSO algorithm for many times, the initial wolf group size and initial fitness value are determined. A nonlinear convergence factor is introduced to balance the exploration and development capabilities of GWO algorithm, and a dynamic inertia weight factor is proposed to ensure the leadership system of alpha wolf and to promote the population communication. Levy flight and greedy strategy are used to effectively avoid the local …
Monitoring Method Research On Passenger Behavior On Escalator Based On Digital Twin, Nan Lü, Qibing Wang, Lu Jiawei, Juntong Chen, Gang Xiao
Monitoring Method Research On Passenger Behavior On Escalator Based On Digital Twin, Nan Lü, Qibing Wang, Lu Jiawei, Juntong Chen, Gang Xiao
Journal of System Simulation
Abstract: In order to solve the problems that the traditional escalator cannot be monitored and analyzed in real time during operation, the management and maintenance only on escalator equipment side, and the lack of monitoring passenger dangerous behavior, a monitoring method of passenger behavior on escalator based on digital twin is proposed. By constructing the digital twin of escalators, a visual interface is designed to map the escalator running status and passenger behavior data. Through passenger video surveillance, the improved OpenPose posture recognition algorithm is used to obtain the key point data of human body. Posture recognition is classified to …
A Compliant Robot Control Based On Extended Social-Force Model For Human-Following And Obstacle Avoidance, Jianwei Peng, Zhelin Liao, Hanchen Yao, Zhiyu Wan, Liqi Zhu, Houde Dai
A Compliant Robot Control Based On Extended Social-Force Model For Human-Following And Obstacle Avoidance, Jianwei Peng, Zhelin Liao, Hanchen Yao, Zhiyu Wan, Liqi Zhu, Houde Dai
Journal of System Simulation
Abstract: Human-robot coexisting is an essential feature of the next generation mobile robot. A compliant robot control strategy based on the extended social-force model for human-following and obstacle avoidance in coexisting-cooperative-cognitive environment is presented. The human-following controller based on impedance control can simultaneously adjust human-robot interaction force and position deviation to carry out the compliant human-following of mobile robots. Considering humanrobot- obstacle interactions, based on the extended social-force model and proxemics, a control strategy for human-friendly compliant human-following and obstacle avoidance is designed to solve the obstacle avoidance problem of robot and ensure the human comfort and improving the social …
Generalization Through Diversity: Improving Unsupervised Environment Design, Wenjun Li, Pradeep Varakantham, Dexun Li
Generalization Through Diversity: Improving Unsupervised Environment Design, Wenjun Li, Pradeep Varakantham, Dexun Li
Research Collection School Of Computing and Information Systems
Agent decision making using Reinforcement Learning (RL) heavily relies on either a model or simulator of the environment (e.g., moving in an 8x8 maze with three rooms, playing Chess on an 8x8 board). Due to this dependence, small changes in the environment (e.g., positions of obstacles in the maze, size of the board) can severely affect the effectiveness of the policy learned by the agent. To that end, existing work has proposed training RL agents on an adaptive curriculum of environments (generated automatically) to improve performance on out-of-distribution (OOD) test scenarios. Specifically, existing research has employed the potential for the …
Learning To Send Reinforcements: Coordinating Multi-Agent Dynamic Police Patrol Dispatching And Rescheduling Via Reinforcement Learning, Waldy Joe, Hoong Chuin Lau
Learning To Send Reinforcements: Coordinating Multi-Agent Dynamic Police Patrol Dispatching And Rescheduling Via Reinforcement Learning, Waldy Joe, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We address the problem of coordinating multiple agents in a dynamic police patrol scheduling via a Reinforcement Learning (RL) approach. Our approach utilizes Multi-Agent Value Function Approximation (MAVFA) with a rescheduling heuristic to learn dispatching and rescheduling policies jointly. Often, police operations are divided into multiple sectors for more effective and efficient operations. In a dynamic setting, incidents occur throughout the day across different sectors, disrupting initially-planned patrol schedules. To maximize policing effectiveness, police agents from different sectors cooperate by sending reinforcements to support one another in their incident response and even routine patrol. This poses an interesting research challenge …
A Hierarchical Optimization Approach For Dynamic Pickup And Delivery Problem With Lifo Constraints, Jianhui Du, Zhiqin Zhang, Xu Wang, Hoong Chuin Lau
A Hierarchical Optimization Approach For Dynamic Pickup And Delivery Problem With Lifo Constraints, Jianhui Du, Zhiqin Zhang, Xu Wang, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We consider a dynamic pickup and delivery problem (DPDP) where loading and unloading operations must follow a last in first out (LIFO) sequence. A fleet of vehicles will pick up orders in pickup points and deliver them to destinations. The objective is to minimize the total over-time (that is the amount of time that exceeds the committed delivery time) and total travel distance. Given the dynamics of orders and vehicles, this paper proposes a hierarchical optimization approach based on multiple intuitive yet often-neglected strategies, namely what we term as the urgent strategy, hitchhike strategy and packing-bags strategy. These multiple strategies …
Imitation Improvement Learning For Large-Scale Capacitated Vehicle Routing Problems, The Viet Bui, Tien Mai
Imitation Improvement Learning For Large-Scale Capacitated Vehicle Routing Problems, The Viet Bui, Tien Mai
Research Collection School Of Computing and Information Systems
Recent works using deep reinforcement learning (RL) to solve routing problems such as the capacitated vehicle routing problem (CVRP) have focused on improvement learning-based methods, which involve improving a given solution until it becomes near-optimal. Although adequate solutions can be achieved for small problem instances, their efficiency degrades for large-scale ones. In this work, we propose a newimprovement learning-based framework based on imitation learning where classical heuristics serve as experts to encourage the policy model to mimic and produce similar or better solutions. Moreover, to improve scalability, we propose Clockwise Clustering, a novel augmented framework for decomposing large-scale CVRP into …
Learning Deep Time-Index Models For Time Series Forecasting, Jiale Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi
Learning Deep Time-Index Models For Time Series Forecasting, Jiale Gerald Woo, Chenghao Liu, Doyen Sahoo, Akshat Kumar, Steven Hoi
Research Collection School Of Computing and Information Systems
Deep learning has been actively applied to time series forecasting, leading to a deluge of new methods, belonging to the class of historicalvalue models. Yet, despite the attractive properties of time-index models, such as being able to model the continuous nature of underlying time series dynamics, little attention has been given to them. Indeed, while naive deep timeindex models are far more expressive than the manually predefined function representations of classical time-index models, they are inadequate for forecasting, being unable to generalize to unseen time steps due to the lack of inductive bias. In this paper, we propose DeepTime, a …
Point Cloud Surface Matching Method Based On Precise Matching Of Critical Point, Xiaojuan Ning, Chunxu Li, Jiahao Wang, Jing Tang, Yinghui Wang, Haiyan Jin
Point Cloud Surface Matching Method Based On Precise Matching Of Critical Point, Xiaojuan Ning, Chunxu Li, Jiahao Wang, Jing Tang, Yinghui Wang, Haiyan Jin
Journal of System Simulation
To solve the low matching efficiency and insufficient accuracy of feature-based point cloud surface matching method during critical point matching, a point cloud surface matching method based on the pairing exaction of critical points is proposed.An improved 3D scale-invariant feature transform(3D-SIFT) algorithm based on curvature information is presented to extract the critical points. Fast point feature histograms(FPFH) feature, the angle between the vector from the center to critical points and the principal direction of the model are taken as the constraints to obtain the exact critical point matching point pair set. The initial matching of the model surface is …
Semantic Segmentation Model Based On Adaptive Fusion And Attention Refinement, Yun Wei, Qi Luo, Yingzhi Zhao
Semantic Segmentation Model Based On Adaptive Fusion And Attention Refinement, Yun Wei, Qi Luo, Yingzhi Zhao
Journal of System Simulation
Aiming at the insufficient use of context information and loss of detail information of the existing semantic segmentation, a model based on adaptive fusion and attention refinement is proposed.The model introduces an adaptive fusion module in the process of coding, and solves the insufficient use of context information by fusing each feature map according to the corresponding weight. An attention thinning module is designed in the process of decoding, so that the low-order features and high-order features can guide and optimize each other to solve the loss of detail information.The experimental results show that the average intersection union …
Fault Indicator Configuration Optimization Based On Cooperative Game Particle Swarm Algorithm, Xu Wang, Weidong Ji, Guohui Zhou
Fault Indicator Configuration Optimization Based On Cooperative Game Particle Swarm Algorithm, Xu Wang, Weidong Ji, Guohui Zhou
Journal of System Simulation
In order to balance the reliability and economy of distribution network fault indicator, a multispace cooperative game particle swarm optimization algorithm is proposed. Based on the idea of population space grouping, the population activity space is adaptively divided, the particle game evolution in subspace is achieved, and the game calculation of particle fusion cosine similar reverse strategy is carried out, which well balances the convergence and diversity of the algorithm. The simulation results show that the adaptive multi-space division of population is conducive to jumping out of the local extreme value, and the game calculation integrating cosine similar reverse is …
Ar-Assisted Sign Language Letter Recognition Method Based On Improved Mobilenet Network, Chunhong Liu, Song Wang, Fupan Wang, Wensheng Tang, Yunqiang Pei, Dongsheng Tian, Yadong Wu
Ar-Assisted Sign Language Letter Recognition Method Based On Improved Mobilenet Network, Chunhong Liu, Song Wang, Fupan Wang, Wensheng Tang, Yunqiang Pei, Dongsheng Tian, Yadong Wu
Journal of System Simulation
An AR-assisted sign language letter recognition algorithm MS-MobileNet is proposed for the problems of sign language gestures needing to be standardized and low recognition rate. A multi-scale convolution module is designed to extract the low-level features and enhance the feature extraction ability. ELU activation function is used to retain the negative feature information, which combined with a lightweight MobileNet model for the web to improve the recognition accuracy and real-time performance for mobile AR applications. Test results show that compared with the original model, the recognition accuracy of MS-MobileNet on the datasets ASL-M, NUS-II and Creative Senz3D is improved by …
Summary Of Simulation Technology And Its Application In Training Field, Zhiming Qiu, Heng Li, Yufang Zhou, Duzheng Qing
Summary Of Simulation Technology And Its Application In Training Field, Zhiming Qiu, Heng Li, Yufang Zhou, Duzheng Qing
Journal of System Simulation
High-tech weapons operations and battlefield environment become more and more increasingly sophisticated. It is an effective way to resolve the conflicts between huge equipment training cost and limited resources and improve training quality by building networked systematic and intelligent simulation training equipment and system and conducting systematic countermeasure simulation training based on present simulation technologies and training resources. The current situation and trend of the development of system architecture of simulation simulation modeling enemy simulation information system simulation etc are evaluated and summarized. It initially analyses the application and efficacy on the US Navy's normalized training environment typical systems such …
Simulation Research On Cooperative Control For Aircraft Ground Deicing Operation, Liwen Wang, Biao Li, Zhiwei Xing, Guan Lian
Simulation Research On Cooperative Control For Aircraft Ground Deicing Operation, Liwen Wang, Biao Li, Zhiwei Xing, Guan Lian
Journal of System Simulation
Aiming at the weak cooperation and low efficiency in aircraft ground deicing operation,a cooperative control method for deicing operations is designed based on the consistency of information states.A two-stage deicing Agent model is proposed and a multi-objective collaborative optimization model with the best deicing effect and the shortest deicing time is established. Lagrangian relaxation algorithm is applied to construct a feasible solution for the optimal operating parameters. Combined with the deicing process and mode, the cooperative graph of deicing operation is studied based on the operating topology, and the cooperative control method of ground deicing is constructed …
Research On Energy Coordination Control Strategy In Dc Microgrid, Zibao Lu, Hao Ding, Fangyun Sun, Ziqiong Ding, Li Gong, Rui Zheng
Research On Energy Coordination Control Strategy In Dc Microgrid, Zibao Lu, Hao Ding, Fangyun Sun, Ziqiong Ding, Li Gong, Rui Zheng
Journal of System Simulation
Aiming of the bus voltage stability and energy flow balance in DC microgrids,a switching control strategy based on the energy balance relationship of DC microgrid is proposed. The bus voltage balance of DC microgrid is transformed into energy balance, and DC microgrid is modeled as a linear switching system with five modes. A controller is designed for each mode to stabilize the bus voltage. To achieve the seamless and smooth switching between modes, on the basis of maintaining the stability of any switching, the corresponding mode switching rules are given based on the energy flow characteristics of microgrid.Theoretical …
An Approach To Solving The Incoming Target Based On Uncertain Time Series, Jing Yang, Minghua Lu, Xingchen Hu, Jinping Wu
An Approach To Solving The Incoming Target Based On Uncertain Time Series, Jing Yang, Minghua Lu, Xingchen Hu, Jinping Wu
Journal of System Simulation
The traditional solution method for the incoming attacking target in water lacks the time series characteristics mining on multi-dimensional and uncertain observation data. Aiming at the time series prediction with high complexity and missing data, a method based on adaptive window interpolation and deep variable weight long-term and short-term memory network model for missing time series observation data with multiple sampling frequencies is proposed, which is compared and verified on the simulation data and public test data set.Aiming at the random missing problem caused by the inconsistency of sampling frequency of multi-source observation information, an adaptive window imputation method …
Particle Swarm Optimization For New Energy Truck Scheduling In Network Environment, Chuanchao Zhao, Rui Zheng, Li Gong, Xiaolu Ma
Particle Swarm Optimization For New Energy Truck Scheduling In Network Environment, Chuanchao Zhao, Rui Zheng, Li Gong, Xiaolu Ma
Journal of System Simulation
In V2X intelligent network environment, the dispatching system of new energy trucks needs real-time dynamic information.The system under traditional particle swarm scheduling method is prone to fall into local optimum and low solution efficienty.An improved particle swarm scheduling method for new energy trucks is proposed on the basis of multi-objective optiminaztion research. The inertia weight update method is improvedso that the inertia weight decreases non-linearly, andthe risk of the system falling into local optimum is reduced.A priori path encoding method is designed and optimized,the solution efficiency of the algorithm is improved, …
Research On Application Of Monarch Butterfly Optimization Particle Filter In Slam, Zhiqiang Chen, Menglong Cao, Wenbin Zhao
Research On Application Of Monarch Butterfly Optimization Particle Filter In Slam, Zhiqiang Chen, Menglong Cao, Wenbin Zhao
Journal of System Simulation
In traditional particle filter resampling, weight degradation and loss of particle diversity are prone to occur, which leads to the decrease in filtering accuracy and result in inaccurate robot positioning and inaccurate mapping. An optimized particle filter algorithm based on the improved monarch butterfly algorithm is proposed.The algorithm replaces the particle individual with the monarch butterfly individual, and integrates the migration operator and adjustment operator in the monarch butterfly algorithm into the particle filter algorithm. The adaptive genetic parameters are introduced to the iterative update process of the monarch butterfly, and the linear combination optimization resampling method is used …
A Uav Target Tracking And Control Algorithm Based On Siamrpn, Songming Jiao, Hui Ding, Yufei Zhong, Xin Yao, Jiahao Jiahao Zheng
A Uav Target Tracking And Control Algorithm Based On Siamrpn, Songming Jiao, Hui Ding, Yufei Zhong, Xin Yao, Jiahao Jiahao Zheng
Journal of System Simulation
Aiming at the requirement of autonomously tracking land moving targets of rotary-wing UAVs, an autonomous and stable UAV tracking and control system that can adapt to the common interference environments such as scale changes, occlusions, and attitude changes is constructed.The system extracts the imaging position of the target in airborne camera through the twin network based on deep learning, and obtains the relative pose of the target. The image processing algorithm is designed to process the icons in the tracking frame, and the yaw angle of UAV relative to the tracking target is obtained, Kalman filter is introduced to …
Application Of Digital Twin In Digital Transformation Of Thermal Power Units, Ze Dong, Wei Jiang, Xiaoyan Wang, Lei Liu
Application Of Digital Twin In Digital Transformation Of Thermal Power Units, Ze Dong, Wei Jiang, Xiaoyan Wang, Lei Liu
Journal of System Simulation
A new state estimation algorithm is proposed to improve the accuracy to obtain the optimal state estimation of distribution network against FDI attack. In the case of phasor measurement units being attacked and the measurement results being alteredthe optimal Kalman estimate can be decomposed into a weighted sum of local state estimates. Focusing on the insecurity of the weighted sum methoda convex optimization based on local estimation is proposed to replace the method and combine the local estimation into a secure state estimation. The simulation results show that the proposed estimator is consistent with the Kalman …