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Articles 31 - 60 of 310
Full-Text Articles in Systems Science
Auv Path Planning Based On Behavior Cloning And Improved Dqn In Partially Unknown Environments, Lijing Xing, Min Li, Xiangguang Zeng, Ping Zhang, Bei Peng
Auv Path Planning Based On Behavior Cloning And Improved Dqn In Partially Unknown Environments, Lijing Xing, Min Li, Xiangguang Zeng, Ping Zhang, Bei Peng
Journal of System Simulation
Abstract: To address the problems of large randomness and slow convergence of the DQN dynamic path planning algorithm for a single autonomous underwater vehicle (AUV) in a partially unknown environment, a path planning method combining behavior cloning with A* algorithm and DQN (BA_DQN) was proposed. Based on the known environmental information, an improved A* algorithm incorporating ocean current resistance was proposed to guide DQN, thereby reducing the randomness of the DQN algorithm. By considering the complexity of the marine environment, the sampling probability was improved again after expanding the positive experience pool to enhance the training success rate. To address …
Twin Modeling Of Gearbox Fault Early Warning System Based On Spatio-Temporal Characteristics, Yuanxing Tian, Zeyin Han, Ning Wang, Baoding Su, Weilin Xiang
Twin Modeling Of Gearbox Fault Early Warning System Based On Spatio-Temporal Characteristics, Yuanxing Tian, Zeyin Han, Ning Wang, Baoding Su, Weilin Xiang
Journal of System Simulation
Abstract: The wind turbine gearbox cannot effectively collect vibration signals under complex faults, which leads to the decline of fault early warning accuracy of wind turbine gearbox. To address this issue, this study investigated the twin modeling of gearbox fault early warning system based on spatio-temporal characteristics. Through the information acquisition subsystem and optical fiber sensing technology, the time sequence and spatial position data of the wind turbine gearbox during operation were collected in real time to obtain spatio-temporal characteristic data. By using the twin space, the collected spatiotemporal characteristic data of the gearbox were transmitted to the virtual space. …
Path Planning For Mobile Robots Based On Improved Artificial Potential Field Algorithm, Chi Zhang, Wei Wei
Path Planning For Mobile Robots Based On Improved Artificial Potential Field Algorithm, Chi Zhang, Wei Wei
Journal of System Simulation
Abstract: In view of the problems of unreachable target areas and easy local minima in traditional artificial potential field methods, an improved artificial potential field method was proposed. The improved algorithm optimized the repulsive field function by introducing obstacle angle factors and distance factors to control the repulsive force magnitude. At the same time, an additional repulsive force towards the target point was added to solve the problem of unreachable target areas in traditional algorithms. When the robot fell into a local minimum, by introducing turning towards obstacles and turning factors to accurately apply escape forces to the robot, the …
Dynamic Supernetwork Modeling Of Command Information System Based On Task Timing, Xuehuan Qiu, Zhiming Dong, Liang Li, Zhuoli Liu
Dynamic Supernetwork Modeling Of Command Information System Based On Task Timing, Xuehuan Qiu, Zhiming Dong, Liang Li, Zhuoli Liu
Journal of System Simulation
Abstract: Due to the difficulty in reflecting the various information activities and interactions within the command information system using general modeling methods for complex system structure, the advantages of supernetwork in characterizing node heterogeneity and link multiplicity of the system were utilized. Based on the research on the mapping mechanism of the command information system across three domains, the dynamic and multifunctional properties of the functional network structure were analyzed. A dynamic supernetwork model based on task timing was constructed considering task requirements, providing model support for further research on complex interaction relationships in the command information system. The dynamic …
Improvement Of Slam Localization Accuracy In Ar By Enhancing Yolov8, Jia Liu, Zengwei Zhang, Dapeng Chen, Nanxuan Huang, Bin Wang, Hong Song
Improvement Of Slam Localization Accuracy In Ar By Enhancing Yolov8, Jia Liu, Zengwei Zhang, Dapeng Chen, Nanxuan Huang, Bin Wang, Hong Song
Journal of System Simulation
Abstract: In the presence of dynamic interference in the environment, traditional simultaneous localization and mapping (SLAM) methods often experience reduced precision and stability in the registration of virtual objects during three-dimensional registration in augmented reality (AR). To address these issues, an improved method for dynamic scenes based on semantic segmentation and optical flow tracking was proposed. The convolutional block attention module (CBAM) attention mechanism was incorporated into YOLOv8 to enhance its focus on dynamic objects in the environment, thereby improving detection performance and accuracy. The semantic segmentation functionality of the improved YOLOv8 was integrated into the front-end of ORB-SLAM3 to …
Cooperative Guidance Method Considering Impact Time And Area Sealing, Zheng Guo, Guofei Li, Hua Xiong, Yunjie Wu
Cooperative Guidance Method Considering Impact Time And Area Sealing, Zheng Guo, Guofei Li, Hua Xiong, Yunjie Wu
Journal of System Simulation
Abstract: To address the problem of multi-vehicle cooperative strike against maneuvering targets, a cooperative guidance method considering impact time control and terminal area sealing was proposed. The distributed disturbance observer was utilized to estimate target maneuvers. Based on the consensus errors of the impact time, the cooperative guidance law in the line-of-sight direction was proposed to achieve simultaneous hits on targets at a specified time. By considering the motion states of targets, the instructions of the terminal area sealing were designed to construct the sliding mode surface and design the line-of-sight guidance law, so as to ensure the convergence of …
Optimization Of Service Caching And Computation Offloading In Digital Twin Cloud-Edge Networks, Jiayu Zheng, Zhuxue Mai, Zheyi Chen
Optimization Of Service Caching And Computation Offloading In Digital Twin Cloud-Edge Networks, Jiayu Zheng, Zhuxue Mai, Zheyi Chen
Journal of System Simulation
Abstract: In mobile edge computing (MEC), to satisfy diverse user demands by jointly optimizing service caching and computation offloading and address low-efficiency resource utilization caused by irrational resource allocation, this paper proposed a novel joint optimization of service caching and computation offloading with a convex-optimization-enabled deep reinforcement learning (JCO-CR) method. Additionally, a new model for digital twin cloud-edge networks (DTCEN) was constructed. The joint optimization of service caching and computation offloading was decoupled into two sub-problems, which were solved by an improved deep reinforcement learning method and convex optimization theory, respectively. Simulation experiments demonstrate that the proposed JCO-CR method …
Attitude Control Of Quadrotor Uav Based On Disturbance Observer And Command Filtering, Boning Li, Ming Chen, Shuchang Qi, Haoran Meng, Lei Wang
Attitude Control Of Quadrotor Uav Based On Disturbance Observer And Command Filtering, Boning Li, Ming Chen, Shuchang Qi, Haoran Meng, Lei Wang
Journal of System Simulation
Abstract: A finite-time fault-tolerant control scheme based on backstepping was proposed for the attitude tracking control problem of quadrotor UAVs. A finite-time neural network disturbance observer was designed, which could quickly compensate for the impacts of actuator failures and external disturbances, thereby enhancing the system's robustness. A first-order command filter and a compensation mechanism were introduced, which could avoid the computational complexity caused by differentiating the virtual control law and eliminate the influence of filtering errors. The hyperbolic tangent function was selected as the constraint function for the input torque, which restricted the input signal to prevent excessive magnitude …
Research On Cgf-Oriented Natural Language Interaction Framework, Xinmeng Li, Kai Xu, Yue Hu, Hesong Huang, Quanjun Yin
Research On Cgf-Oriented Natural Language Interaction Framework, Xinmeng Li, Kai Xu, Yue Hu, Hesong Huang, Quanjun Yin
Journal of System Simulation
Abstract: To address the mismatch between existing natural language interaction frameworks and training tasks in simulation-based military training, which limits smooth interaction between trainees and Computer Generated Forces (CGF), this paper proposes a Natural Language Interaction framework for Computer Generated Forces (NLI4CGF). The framework analyzes the logic and functional requirements of natural language interaction between trainees and CGF, and establishes an interaction architecture tailored for military simulation training scenarios. It supports semantic parsing and knowledge query tasks within a prototype system developed for infantry squad simulation training. Experimental results demonstrate that the proposed model performs effectively, meets the requirements of …
Parking Space Reasoning Model For Complex Scenarios, Congling Zhou, Chunpeng Wang, Qiwei Xie, Yongqiang Wang, Lijun Shen
Parking Space Reasoning Model For Complex Scenarios, Congling Zhou, Chunpeng Wang, Qiwei Xie, Yongqiang Wang, Lijun Shen
Journal of System Simulation
Abstract: In the industrialization process of the combined driving assistance system, complex parking environments bring many challenges, such as occlusion of parking spaces, uneven lighting, and missed and false detections. To address these issues, a parking space reasoning model named PIPS-Net was proposed through PINet optimization. In terms of network architecture design, the model deeply integrated the stacked hourglass network with the recurrent feature-shift aggregator (RESA) to construct a context feature extraction architecture, which enhanced the feature reasoning ability in complex scenarios. Meanwhile, it reconstructed the output to meet the requirements of parking space detection tasks, thereby jointly improving the …
Research On Vehicle Path Optimization Algorithms For Urban Logistics And Distribution, Zhenpeng Ma, Hanyang Jiao, Zhe Zhang, Cheng Liu, Bo Jiang, Lin Wang
Research On Vehicle Path Optimization Algorithms For Urban Logistics And Distribution, Zhenpeng Ma, Hanyang Jiao, Zhe Zhang, Cheng Liu, Bo Jiang, Lin Wang
Journal of System Simulation
Abstract: Existing optimization algorithms for solving the vehicle routing problem with time windows (VRPTW) are prone to fall into local optimal solutions and have slow convergence speed. To address this issue, a K-means clustering algorithm and improved large neighborhood search algorithm (K-means-ILNSA) was proposed. A strategy of clustering before optimization was adopted, and the K-means algorithm was adopted to group the customers to be delivered, so as to improve the optimization efficiency. The genetic algorithm was adopted to optimize each group of customers generated by clustering separately to initially plan the distribution routes. The large neighborhood search (LNS) algorithm was …
Bayesian Network Parameter Learning Based On Ahp-Dst Fusion Of Expert Prior Knowledge, Haiyang Chen, Hongkai Lin, Zhifang Ren, Jing Liu, Jing Zhang
Bayesian Network Parameter Learning Based On Ahp-Dst Fusion Of Expert Prior Knowledge, Haiyang Chen, Hongkai Lin, Zhifang Ren, Jing Liu, Jing Zhang
Journal of System Simulation
Abstract: Aiming at the problem of low accuracy of BN parameter learning due to the uncertainty of a single expert prior knowledge under the condition of small sample data set, a BN parameter learning method based on AHP-DST fusion expert prior knowledge was designed. The synthetic prior knowledge of experts was calculated by using the thought of analytic hierarchy process combined with the rules of evidence theory synthesis. The expert comprehensive prior knowledge was added to the normal distribution and combined with the monotonicity constraint to obtain the virtual sample information. The virtual sample information was added to the Bayesian …
Research On Path Smoothing Processing Of Mobile Robot Based On Improved A* Algorithm, Mengyuan Chen, Guifang Qiao, Xu Zou, Jiayu Cao, Lei Tian
Research On Path Smoothing Processing Of Mobile Robot Based On Improved A* Algorithm, Mengyuan Chen, Guifang Qiao, Xu Zou, Jiayu Cao, Lei Tian
Journal of System Simulation
Abstract: Traditional bidirectional A* algorithm has many path inflection points, undergoes smoothness, and faces diagonal obstacles in path traversing. Therefore, an improved bidirectional A* algorithm was proposed. Local path constraint search was added to the forward search and backward search, respectively to solve the problem of planning paths traversing diagonal obstacles, and the effectiveness of the improved bidirectional A* algorithm to avoid traversing diagonal obstacles was verified through simulations. The path inflection points were optimized by introducing the cubic B-spline curve, and the paths before and after smoothing were tracked and controlled, respectively by using the differential-driven mobile robot. The …
Boolean Network Model Optimization Based On Neural Network And Genetic Programming, Jinlin Tang, Yan Wang, Xiang Liu, Tuanjie Wang, Zhicheng Ji
Boolean Network Model Optimization Based On Neural Network And Genetic Programming, Jinlin Tang, Yan Wang, Xiang Liu, Tuanjie Wang, Zhicheng Ji
Journal of System Simulation
Abstract: To address the issues of complex node relationships and low accuracy in large-scale Boolean network inference, a new optimization algorithm integrated with long short-term memory (LSTM) networks and genetic programming was proposed. An enhanced LSTM network combined with a self-attention mechanism was designed to extract potential regulatory nodes from time-series data. These nodes were utilized as terminals of the syntax tree for the design of the genetic programming algorithm, and new operators were introduced to optimize Boolean function search. Experimental results have demonstrated that the proposed method significantly outperforms the most advanced existing algorithms in inference accuracy. The Boolean …
Self-Calibrating Passenger Flow Simulation And Spatial Optimization For Public Building Based On Gru-Sa, Jinglin Xu, Qianru Chen, Yang Peng, Fangqiang Yu
Self-Calibrating Passenger Flow Simulation And Spatial Optimization For Public Building Based On Gru-Sa, Jinglin Xu, Qianru Chen, Yang Peng, Fangqiang Yu
Journal of System Simulation
Abstract: Real-time and precise passenger flow simulation provides critical data support for the optimal allocation of resources in public building facilities and the rational design of spatial layouts. This study proposed a self-calibrating passenger flow simulation and spatial optimization method for public buildings based on the GRU-simulated annealing algorithm. A simulation model incorporating spatial structures and flow lines was constructed using Anylogic. A self-calibrating passenger flow simulation method for public buildings was designed based on the GRU-simulated annealing algorithm and applied to the outpatient department of a hospital in Shanghai for passenger flow simulation. The effectiveness of the method was …
Image Feature Point Matching Algorithm Based On Attention And Hierarchical Features, Na Chen, Jiajia Bai, Qiyin Zhou, Jialin Li
Image Feature Point Matching Algorithm Based On Attention And Hierarchical Features, Na Chen, Jiajia Bai, Qiyin Zhou, Jialin Li
Journal of System Simulation
Abstract: Feature point detection and matching is one of the core technologies in the field of intelligent driving. Aiming at the lack of consistency and continuity of feature points extracted by the existing algorithms, as well as the problem of easily ignoring the contextual semantic information when matching, this paper proposes an image feature point matching algorithm based on attention and hierarchical features (AHMF). In the feature point detection stage, differential interaction attention module (DIAM) is proposed to enhance the model's attention to the salient regions so as to improve the robustness of the feature points; further introduction of hierarchical …
Evolutionary Reinforcement Learning Based On Elite Instruction And Random Search, Jian Di, Xue Wan, Limei Jiang
Evolutionary Reinforcement Learning Based On Elite Instruction And Random Search, Jian Di, Xue Wan, Limei Jiang
Journal of System Simulation
Abstract: Evolutionary reinforcement learning currently suffers from low sample efficiency, a single coupling method, and poor convergence, which can affect its performance and scaling. To address this issue, an improved algorithm based on elite gradient instruction and double random search was proposed. The direction of the reinforcement strategy gradient update was corrected by introducing elite strategy gradient guidance carrying evolutionary information during reinforcement strategy training. Double stochastic search was used to replace the original evolutionary component, reducing the complexity of the algorithm while making the policy search meaningful and controllable in the parameter space. The introduction of complete replacement information …
Research On Temperature Compensation Technology Of Fiber Optic Gyroscope Based On Iscso-Bp Neural Network Model, Zhili Zhang, Jin Liu, Zhaofa Zhou, Zhe Liang, Yunhao Zhang
Research On Temperature Compensation Technology Of Fiber Optic Gyroscope Based On Iscso-Bp Neural Network Model, Zhili Zhang, Jin Liu, Zhaofa Zhou, Zhe Liang, Yunhao Zhang
Journal of System Simulation
Abstract: To address the issue that changes in ambient temperature significantly affect the output accuracy of the fiber optic gyro (FOG), which causes zero bias drift, increases measurement errors, and limits their application accuracy in complex environments, a temperature compensation model based on BP neural networks was proposed. To improve the performance of neural networks, the sand cat swarm optimization (SCSO) was improved, and the improved SCSO (ISCSO) was used to optimize the weights and thresholds of BP neural networks. Experimental results show that using the ISCSO-BPNN temperature compensation model to compensate for the gyro's temperature errors significantly improves the …
Research On Time Sequence Design Method Of Dynamic Simulation Scene For Starlight Navigation, Xiaoting Su, Xiaowei Zhang, Yi Tian, Qi Li, Shuaihao Wang
Research On Time Sequence Design Method Of Dynamic Simulation Scene For Starlight Navigation, Xiaoting Su, Xiaowei Zhang, Yi Tian, Qi Li, Shuaihao Wang
Journal of System Simulation
Abstract: To solve the problem of misidentification of star maps due to time sequence mismatch in the hardware-in-the-loop simulation system of star navigation, where star trackers with different shutter types (global shutter and rolling shutter) and star simulators with varying refresh display methods (whole frame refresh and line sweep refresh) operated without synchronization, a time sequence design method of the dynamic simulation scene for starlight navigation without the need of external synchronization signals was proposed. The method could design the refresh frequency and duty cycle of the corresponding star simulators according to the detector integration time of the tested star …
Robot Path Planning Optimization Based On Fusion Of Improved Ant Colony Algorithm And A* Algorithm, Lanying Yang, Chao Li, Haifeng Zou, Jiangtao Wan, Renqiang Zhang, Hui Liu, Hong Lu
Robot Path Planning Optimization Based On Fusion Of Improved Ant Colony Algorithm And A* Algorithm, Lanying Yang, Chao Li, Haifeng Zou, Jiangtao Wan, Renqiang Zhang, Hui Liu, Hong Lu
Journal of System Simulation
Abstract: To improve slow search efficiency and achieve real-time obstacle avoidance in traditional ant colony algorithms, an adaptive ant colony algorithm was proposed. A guidance direction mechanism was introduced to shorten the time of node selection. The A* algorithm's path-finding mechanism was introduced into the heuristic function to reduce the length and number of circles of the optimal path solution. The route planned by the traditional A* algorithm was used as the initial iteration data of the ant colony algorithm in global path planning, so as to solve the problem of slow initial convergence of the ant colony algorithm. The …
Secret Key Generation Based On The Physical Layer Characteristics For Iot Networks, Abdullah Dakhlallah Alshamdayn
Secret Key Generation Based On The Physical Layer Characteristics For Iot Networks, Abdullah Dakhlallah Alshamdayn
Doctoral Dissertations
The rapid expansion of low-resource devices, coupled with advances in telecommunications, has significantly increased the number of connected devices and enabled the development of affordable, energy-efficient, portable, and high-performance sensors for diverse applications. However, this convenience comes with security and privacy concerns related to the reliability of hardware, software, and communication infrastructure. The extensive interconnectivity of limited-resource devices and the transmission of large data volumes pose significant security challenges in wireless networks. The future wireless technologies, such as 5G, will enable the transfer of critical data, including personal, financial, military, and industrial information, necessitating secure communication in wireless networks. Generally, …
Shifted Frequency Analysis Hybrid Simulation Algorithm Based On Multi-Rate Asynchronous Coordination, Yankan Song, Libin Wen, Ying Chen, Jinji Xi, Haoyuan Zhang, Li Xiong
Shifted Frequency Analysis Hybrid Simulation Algorithm Based On Multi-Rate Asynchronous Coordination, Yankan Song, Libin Wen, Ying Chen, Jinji Xi, Haoyuan Zhang, Li Xiong
Journal of System Simulation
Abstract: Large-scale AC/DC power systems exhibit complex dynamics across multiple time scales, and existing hybrid simulations suffer from interface delays and frequency losses during multi-rate coordination, compromising accuracy. To address this issue, a multi-rate asynchronous coordination method was proposed to construct hybrid simulations using shifted frequency analysis (SFA). Within the multi-area Thevenin equivalence (MATE) framework, the algorithm introduced an interpolation-based asynchronous coordination mechanism, effectively eliminating interface delays; by extending SFA theory and designing a universal interface model, it achieved lossless data exchange between partitions with different rates and model types. Case studies on an AC/DC test system demonstrate that …
Soft Sensor Modeling Based On Improved Transformer In Dual-Stream Framework, Hao Gu, Jiayu Wang, Weili Xiong
Soft Sensor Modeling Based On Improved Transformer In Dual-Stream Framework, Hao Gu, Jiayu Wang, Weili Xiong
Journal of System Simulation
Abstract: Industrial process information is highly nonlinear and dynamic, with long-term dependencies between data, making it difficult to adequately extract time-series features. To address this issue, an improved Transformer-based soft sensor model in a dual-stream framework was proposed. The data were segmented and expanded. The features were extracted in parallel using a dual-stream structure combining a convolutional neural network with a self-attention mechanism and the improved Transformer model. The dual-stream features were fused for soft sensor regression. Residual connections were further introduced to accelerate the convergence speed of the model, and an orthogonal random features-based improved multi-head attention mechanism was …
Path Planning Of Improved Rrt Algorithm Based On Deep Reinforcement Learning, Xiuman Liang, Ziliang Liu, Zhendong Liu
Path Planning Of Improved Rrt Algorithm Based On Deep Reinforcement Learning, Xiuman Liang, Ziliang Liu, Zhendong Liu
Journal of System Simulation
Abstract: To address the low planning efficiency, poor safety, and limited practicability of the RRT algorithm in global path planning within complex three-dimensional environments, which fail to meet the requirements of planning the safe flight path of UAVs, an improved SAC-RRT algorithm was proposed, which fused SAC deep reinforcement learning algorithm and RRT algorithm. A target point bias strategy and a dynamic step size based on the SAC decision-making network were designed to reduce the blindness of RRT. A random point correction process was designed to optimize the position of random points based on actions from the decision network and …
Low-Energy Multi-Robot Path Planning Algorithm Under Hca* Framework, Ning Wang, Jianlin Mao, Dayan Li, Chengyuan Fang, Chengze Qian
Low-Energy Multi-Robot Path Planning Algorithm Under Hca* Framework, Ning Wang, Jianlin Mao, Dayan Li, Chengyuan Fang, Chengze Qian
Journal of System Simulation
Abstract: To address the energy optimization problem in multi-robot path planning, this paper proposed a multi-robot path planning algorithm based on the energy-guided hierarchical cooperative A* (E-HCA*) algorithm. To address the issue of robot oscillations caused by mutual avoidance at bottlenecks and narrow passages in multi-robot systems, a node expansion method with path length as a secondary feature was introduced, and a greedy suppression strategy under the cooperative A* framework was proposed. A differential-drive robot energy consumption model was established, and an energy-guided heuristic function was constructed by integrating energy metrics into the underlying A* algorithm to guide low-energy path …
Multi-Objective Optimization Of Signal Timing At Intersections Considering Tailpipe Emissions, Xinhuan Ding, Huaqing Wang, Xu Dang
Multi-Objective Optimization Of Signal Timing At Intersections Considering Tailpipe Emissions, Xinhuan Ding, Huaqing Wang, Xu Dang
Journal of System Simulation
Abstract: In order to alleviate urban road congestion and improve the traffic and environmental benefits at intersections, a multi-objective timing optimization model with total delay time, total number of stops, capacity, and total tailpipe emission at intersections as optimization objectives was developed. The model incorporated tailpipe emissions into a mathematical optimization model and quantified the mathematical relationship between traffic efficiency indicators and tailpipe emissions by constructing a specific power-based algorithm for measuring total tailpipe emissions. According to the intersection delay time and the number of stops, the total tailpipe emissions could be estimated. Both the NDX crossover operator and the …
Multisource Information Fusion Method For Human Gait Perception, Guiliang Chen, Guowei Liu, Yongchao Li, Chao Cai, Zihao Li, Dong Yang
Multisource Information Fusion Method For Human Gait Perception, Guiliang Chen, Guowei Liu, Yongchao Li, Chao Cai, Zihao Li, Dong Yang
Journal of System Simulation
Abstract: In response to the insufficient gait perception capability during lower limb exoskeleton assistance, a human lower limb gait phase optimization classification model was proposed. A wireless transmission gait information collection system was designed for collecting the required gait phase feature information. Human joint angles were accurately calculated by fusing acceleration and angular velocity information using extended Kalman filtering. Additionally, kernel principal component analysis was applied to reduce dimensionality in conjunction with plantar pressure data. The LSSVM algorithm was employed to classify gait data, and the PSO algorithm was utilized to find the optimal classification parameters. Experimental results demonstrate that …
Optimal Scheduling Of Integrated Energy Systems Considering Source-Load Uncertainty And Linear Carbon Trading, Huaping Zhong, Yubo Fan, Jijun Shui, Danhao Wang, Daogang Peng
Optimal Scheduling Of Integrated Energy Systems Considering Source-Load Uncertainty And Linear Carbon Trading, Huaping Zhong, Yubo Fan, Jijun Shui, Danhao Wang, Daogang Peng
Journal of System Simulation
Abstract: In order to overcome the impact of source-load uncertainty on the scheduling of integrated energy systems (IES) and reflect the flexibility of the carbon trading price with the change in trading volume, an optimal scheduling method for integrated energy systems considering source-load uncertainty and linear carbon trading was proposed. The equipment within the IES was modeled, and nonparametric kernel density estimation was used to obtain the probability density function for each time period, generating the set of scenes through Monte Carlo simulation and calculating the probability of each scene. For the time shift of wind and solar output peaks …
Simulation Of Three-Degree-Of-Freedom Internal Mode Sliding Mode Control For Non-Ideal Single-Inductor Dual-Output Boost Converter, Bingli Liu, Jiarong Wu, Lin Yang, Dinglin Yan
Simulation Of Three-Degree-Of-Freedom Internal Mode Sliding Mode Control For Non-Ideal Single-Inductor Dual-Output Boost Converter, Bingli Liu, Jiarong Wu, Lin Yang, Dinglin Yan
Journal of System Simulation
Abstract: To reduce the cross-interference in the single-inductor dual-output (SIDO) Boost converter and to enhance the output accuracy and stability of the system, the parasitic resistances of the circuit components were considered, and a three-degree-of-freedom internal model sliding mode control strategy was proposed for the non-ideal SIDO Boost converter. An affine nonlinear mathematical model of the non-ideal SIDO Boost converter was established, and the nonlinear system was linearized and decoupled into two linear subsystems based on the differential geometry theory. The linear subsystem was designed as a three-degree-of-freedom internal model controller and a sliding mode controller, respectively. The robustness …
A Novel Joint Training Simulation Evaluation Framework And Its Key Techniques, Rusheng Ju, Dongdong Chen, Yunxiu Zeng, Jiyuan Liu, Sihang Qiu, Peng Zhou
A Novel Joint Training Simulation Evaluation Framework And Its Key Techniques, Rusheng Ju, Dongdong Chen, Yunxiu Zeng, Jiyuan Liu, Sihang Qiu, Peng Zhou
Journal of System Simulation
Abstract: To address the challenges of traditional evaluation systems, such as internal module coupling, lack of reusability, and poor adaptability to multi-domain evaluation needs, a three-tier decoupled technical evaluation framework of "data + service + application" was designed. A strategy was proposed for extracting high-value information from massive audio and video data based on key events, resolving the problem of unstructured evaluation data processing. A design method combining general and dedicated evaluation model templates was proposed, improving the general applicability of the evaluation model. An expert knowledge-driven comprehensive integrated discussion and evaluation environment was constructed using qualitative and …