Parameter Identification Of Permanent Magnet Synchronous Motors Based On Igwo-Aekf,
2026
School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Parameter Identification Of Permanent Magnet Synchronous Motors Based On Igwo-Aekf, Lei Yao, Zijian Zheng, Tianhao Li, Yulun Chi
Journal of System Simulation
The accuracy of the traditional EKF in parameter identification of the PMSM tends to be degraded under load changes or abrupt changes in internal parameters of the motor. This paper proposes an IGWO adaptive interconnected Kalman filter observer, which constructs an adaptive mechanism that combines the innovation and residuals to achieve dynamic adjustment of the process noise matrix and system noise matrix, thereby avoiding the problem of reduced parameter identification accuracy due to reliance on fixed covariance matrices under operating condition changes. A multi-parameter interconnected coupling compensation identification model for PMSM is built to mitigate the effects of measurement noise …
Research On Control Strategy For Shortest Time Occupancy Of Auv Based On Improved Td3,
2026
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China
Research On Control Strategy For Shortest Time Occupancy Of Auv Based On Improved Td3, Wenzhe Ren, Min Li, Xiangguang Zeng, Tao Zhang, Dijie Xie, Bei Peng
Journal of System Simulation
Existing occupancy models fail to fully consider the interference of underwater time-varying ocean currents and task time constraints, and AUVs lacks real-time motion control. To address these issues, a shortest time occupancy method based on quantile regression and distributed TD3 was proposed. The Bayesian inference method was used to identify hydrodynamic parameters, and the kinematic and dynamic models of AUVs were established; the shortest time occupancy equation was constructed, and the occupancy target point and occupancy time were solved; a first-order Gauss-Markov process was introduced to simulate the time-varying ocean current environment, and the training of control strategy for AUV …
Impact Angle-Constrained Dive Maneuver Guidance Method For Hypersonic Vehicles,
2026
School of Missile Engineering, Rocket Force University of Engineering, Xi'an 710025, China
Impact Angle-Constrained Dive Maneuver Guidance Method For Hypersonic Vehicles, He Wang, Gang Lei, Shaopeng Li
Journal of System Simulation
To address the impact angle control and maneuvering flight problem of hypersonic vehicles in the dive phase, this paper proposed a tracking guidance method integrating optimal Bézier curves and super-twisting sliding mode control. A three-dimensional Bézier curve trajectory satisfying the impact angle constraint was designed, and the maneuvering flight in dive phase was achieved by adding dynamic control points; to optimize impact velocity, a rapid calculation method for the impact velocity of the vehicle flying along the curve was derived, and the optimal reference trajectory was obtained by optimizing the control point parameters through sequential quadratic programming; to ensure …
Two-Stage Calibration And Optimization Method For Microscopic Traffic Simulation Model Parameters Based On Neural Network Surrogate Models,
2026
School of Civil Engineering and Transportation, Guangzhou University, Guangzhou 510700, China
Two-Stage Calibration And Optimization Method For Microscopic Traffic Simulation Model Parameters Based On Neural Network Surrogate Models, Yijia Liu, Chenjing Zhou, Dong Pan, Jian Rong, Yang Xiao
Journal of System Simulation
A two-stage calibration and optimization method is proposed to address the problem that parameter calibration methods for microscopic traffic simulation models are time-consuming. In the first stage, a surrogate model based on neural networks is trained to establish the mapping relationship between model parameters and evaluation indicators, and a genetic algorithm (GA) is combined to screen candidate parameters. In the second stage, after obtaining the approximate optimal parameters, by employing this set of parameters as initial values, a genetic algorithm is re-executed by combining the real simulation model for optimization to further improve calibration accuracy. Experimental results show that the …
Application Of Improved Multi-Objective Differential Algorithm In Robotic Arm Multi-Objective Trajectory Planning,
2026
School of Automation and Electrical Engineering, Lanzhou University of Technology, Lanzhou 730000, China
Application Of Improved Multi-Objective Differential Algorithm In Robotic Arm Multi-Objective Trajectory Planning, Manqiang Liu, Ziqiang Shang
Journal of System Simulation
It is difficult for single-objective trajectory planning methods to meet the requirements of precision, diversity and complexity of robotic arms. A trajectory planning model based on an improved multi-objective differential evolution algorithm (guided multi-objective differential evolution, GMODE) algorithm is proposed. Cubic polynomial interpolation and B-spline curves are employed to construct multi-objective functions, while GMODE is adopted to overcome the limitations of traditional algorithms, such as insufficient population diversity, the tendency to fall into local optima, and slow convergence. A grouping strategy, parameter generation mechanism, and elite mutation based on fuzzy Cmeans clustering are introduced to optimize B-spline control nodes. …
Current Status And Prospects Of Complex Scene Reconstruction Based On Gaussian Splatting,
2026
College of Artificial Intelligence & Computer Science, Xi'an University of Science and Technology, Xi'an 710054, China; State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China
Current Status And Prospects Of Complex Scene Reconstruction Based On Gaussian Splatting, Hong'an Li, Jiale Yang, Qingfang Liu, Yu Shi
Journal of System Simulation
Three-dimensional Gaussian splatting (3DGS) provides an alternative approach for novel view synthesis from the perspective of explicit representation. By reconstructing scenes using 3D Gaussian primitives and replacing traditional ray integration with a point-based rasterization process, it not only improves training and rendering efficiency but also offers new insights for complex scene reconstruction. This paper divided 3DGS-based complex scene reconstruction methods into three major categories and elaborated on them around large-scale scenes, sparse views, and dynamic scenes. It reviewed the current development status of this field and pointed out possible future research directions.
Experimental And Simulation Study On Energy Release Of Extended Sources Influenced By Atmospheric Pressure Variation,
2026
Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710000, China; Academy of Opto-Electronic, China Electronic Technology Group Corporation (AOE CETC), Tianjin 300308, China
Experimental And Simulation Study On Energy Release Of Extended Sources Influenced By Atmospheric Pressure Variation, Kai Guo, Feiyu Zhao, Hao Zhang, Liang Wang, Kai Zhang
Journal of System Simulation
To investigate the energy release characteristics of extended sources in low-pressure environments, a combined experiment and simulation approach was adopted. Four typical altitudecorresponding pressures were selected as experimental conditions. An infrared thermal imager was employed to monitor parameters such as combustion temperature, radiance, and combustion area during the combustion process of the extended source. When the pressure decreases from 101 kPa to 30 kPa, the ignition time of the extended source doubles; the total energy release attenuates by 44.78%, and the combustion area reduces by 45.95%, but the fluctuations of peak temperature and average temperature are less than 3%, …
Research On Output Feedback Control Based On Reinforcement Learning For Overhead Crane,
2026
School of Technology, Beijing Forestry University, Beijing 100083, China
Research On Output Feedback Control Based On Reinforcement Learning For Overhead Crane, Minghui Li, Daoxiang Gao
Journal of System Simulation
An output feedback control algorithm is designed based on reinforcement learning for the optimal control problem of overhead crane system. A high gain observer (HGO) is designed using output data to estimate the unmeasurable states of the overhead crane system. Based on the estimated states from the high-gain observer, a policy iteration (PI) method is designed with integral reinforcement learning, which uses Critic and Actor neural networks to approximate the optimal value function and control strategy, and adjusts the neural network weights in real time through online adaptive algorithms. According to the Lyapunov stability theory, the uniform ultimate boundedness of …
Object Detection Networks And Their Interpretability In Rain, Fog, And Snow Scenarios,
2026
Liaoning Technical University, Huludao 125105, China
Object Detection Networks And Their Interpretability In Rain, Fog, And Snow Scenarios, Yanji Jiang, Jiayu Cui, Hao Dong, Daqian Liu, Bowen Fei, Miao Yu, Jinshan Huang
Journal of System Simulation
To address the severe degradation of object detection performance under extreme weather conditions, a detection framework based on the Kolmogorov-Arnold theorem, termed KADet, is proposed. A dynamic Kolmogorov-Arnold Transformer is designed, which leverages learnable nonlinear activation functions to enhance the modeling capability for complex distortions introduced by weather degradation. A Kolmogorov-Arnold spatial-channel network is developed by integrating KAT convolution with spatial-channel convolution to strengthen feature learning of relationships between targets and backgrounds in degraded scenes. An improved loss function is introduced to guide the optimization of the activation functions, and interpretability is analyzed through visualization of their curves. …
Pattern Identification And Mechanism Analysis Of Nonlinear Oscillations In Grid-Connected Direct-Drive Wind Turbines,
2026
Electric Power Research Institute, Guangxi Power Grid Co. , Ltd. , Nanning 530023, China; Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, Nanning 530023, China
Pattern Identification And Mechanism Analysis Of Nonlinear Oscillations In Grid-Connected Direct-Drive Wind Turbines, Libin Wen, Shaopu Tang, Xianfa Hu, Jinji Xi, Tongtong Zhang, Hong Hu, Weijie Zhang
Journal of System Simulation
Taking a grid-connected direct-drive wind turbine system as an example, a comprehensive model is developed that incorporates nonlinear elements such as prime mover control, machine-side and grid-side converter control, multiple limiters, and control switching. A nonlinear oscillation pattern identification method based on density clustering and manual identification is proposed. The results show that the proposed method can efficiently identify various typical patterns, including quasi-constant amplitude oscillations, period-doubling oscillations, and chaotic oscillations. Oscillations dominated by nonlinear factors such as control switching, limiter collision, and limiter saturation are essentially caused by the transition of the associated components from passive responses to …
Iterative Evolution And Innovation Of Simulation-Based Experimental Teaching In Software Engineering,
2026
Software College of Northeastern University, Shenyang 110169, China
Iterative Evolution And Innovation Of Simulation-Based Experimental Teaching In Software Engineering, Jun Guo, Yixian Liu, Lianbo Ma, Jian Liu, Chunyan Xu
Journal of System Simulation
In view of the structural disconnection between talent training and industry needs caused by the limitations of traditional computer experiment teaching in scenario authenticity, technological frontier, interdisciplinary integration, and student subjectivity, this paper proposed and practiced a new simulation-based experimental teaching system deeply integrating Chinese educational wisdom. Taking "incremental progress and learning by guided inquiry" as the core philosophy, through a four-in-one paradigm transformation of "task modularization, scenario virtualization, technological frontier, and integration deepening", this paper promoted the teaching to shift from closed skill verification to open engineering innovation and constructed a complete implementation path including "closed-loop iterative teaching process" …
Robot Friction Force Compensation Algorithm Integrating Temperature And Speed Factors,
2026
Ningbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, China; Ningbo Cixi Institute of Biomedical Engineering, Ningbo 315300, China
Robot Friction Force Compensation Algorithm Integrating Temperature And Speed Factors, Jinwang Lü, Ankai Ying, Ming Li, Tao Song, Jie Zhang, Fanghui Qiu, Changcheng Shi, Guokun Zuo, Jialin Xu
Journal of System Simulation
Insufficient friction force compensation accuracy degrades motion smoothness, stability, and assistive compliance of elbow joint rehabilitation robots. To address this issue, an improved Stribeck friction force model integrating temperature and speed factors was proposed. The model employed an exponentially decaying friction factor to describe the characteristic that the increase rate of friction force slowed down with the rise of the robot's operating speed and designed a viscous function considering temperature effects to suppress friction force fluctuations caused by temperature changes. Experimental results indicate that the model achieves stable friction force compensation under different operating states of the robot and has …
Integrating Production And Repair Operations Through Data Driven Defect Flow Analytics For Yield And Resource Optimization In Pcba Manufacturing,
2026
Binghamton University--SUNY
Integrating Production And Repair Operations Through Data Driven Defect Flow Analytics For Yield And Resource Optimization In Pcba Manufacturing, Ali Tahmasebi, Yingge Zhou, Daryl Santos, Sai Srikanth Reddy Kolli, Edward Wong
Systems Science and Industrial Engineering Student Scholarship
In Printed Circuit Board Assembly (PCBA) manufacturing, maintaining a closed loop connection between production and repair operations is critical to improving product quality and operational efficiency. However, in the manufacturing environment that motivated this work, production and repair data are often managed separately, and repair findings are not systematically fed back to production teams, limiting visibility into defect routing patterns and repair workload drivers. This study developed a data-driven framework that integrates production and repair data streams to analyze defect flow and support repair resource planning. The framework applies descriptive statistics, cross tabulations of repair inflow by product/project and repair …
Can Generative Ai Make Farming Decisions? Current Status And Future Pathways: A Case Study In Row Crop Production With Chatgpt,
2026
University of Nebraska-Lincoln
Can Generative Ai Make Farming Decisions? Current Status And Future Pathways: A Case Study In Row Crop Production With Chatgpt, Nipuna Chamara, Yufeng Ge, Joe Luck, Yu Pan, Saleh Taghvaeian, Cory Walters, Christopher Proctor, Daran Rudnick, Daren Redfearn
Department of Agricultural and Biological Systems Engineering: Faculty Publications
The agricultural decision-making process is experience-based, knowledge-dependent, time-sensitive, complex, and driven by historical data. Planting, fertilization, irrigation, and chemigation are key categories in farm decision-making, and currently there is no one-shot decision-support tool that covers all these activities. Generative Artificial Intelligence (AI) models are more advanced than traditional machine learning and deep learning models. These models have been trained on vast amounts of data from the internet, allowing them to accept unstructured data in various forms and generate human-like text, solutions to problems, and scenario predictions. Given this capability, we became interested in exploring the potential of generative AI in …
Measuring Stock Market Inefficiency Using A Multilayer Composite Efficiency Index: A Case Of The Egyptian Exchange,
2026
Binghamton University--SUNY
Measuring Stock Market Inefficiency Using A Multilayer Composite Efficiency Index: A Case Of The Egyptian Exchange, Patrick K. Owido, Hiroki Sayama
Northeast Journal of Complex Systems (NEJCS)
Financial markets play a critical role in resource allocation. Their performance depends on the decisions of millions of independent investors constantly reacting to one another. Their informational efficiency remains a subject of debate across economic systems. When informational efficiency is present at the weak form, historical price information should not consistently predict future returns. Several empirical tests of this hypothesis often focus on the behavior of aggregate market indices, and use individual efficiency proxies such as autocorrelation, GARCH-type volatility, or entropy-based measures to measure efficiency. This has often yielded mixed results, particularly in emerging markets. Here we show that testing …
Automatic Speed Guidance Method And Simulation Evaluation For Trams At Intersections,
2026
College of Transportation, Tongji University, Shanghai 201804, China; Shanghai Collaborative Innovation Research Center for Multi-network & Multi-modal Rail Transit, Shanghai 201804, China
Automatic Speed Guidance Method And Simulation Evaluation For Trams At Intersections, Jing Teng, Wencong Tong, Zhongjie Zhang, Xing Yao, Junxian Li
Journal of System Simulation
To address the lack of speed regulation mechanism and the high dispersion of operational time in the current manual driving mode, this paper proposes an automatic speed guidance method for trams at intersections. Considering the speed disturbances caused by potential traffic conflicts at intersections, an initial decision point for safe passage speed at an intersection is established, dividing the operational curve into deterministic segments and disturbance-response segments.To verify the effectiveness of the method, a case study of Songjiang Tram Line 1 is conducted.Driving simulation experiments are performed to obtain manual driving trajectories, and a dynamic trajectory simulation model …
Capacity Market Trading Strategies Of Generators Based On Per-Maddpg Algorithm,
2026
School of Economics and Management, North China Electric Power University, Beijing 102206, China
Capacity Market Trading Strategies Of Generators Based On Per-Maddpg Algorithm, Yanbin Li, Zhaolun Pan, Xinyue Ma, Minghao Song, Yujie Hu, Xiaoda Xue
Journal of System Simulation
Considering the issue of how power generators trade off their quantity and price bidding strategies to maximize profits in different capacity market environments, a capacity market bidding equilibrium model is constructed. Recognizing the limitations of traditional solution methods, which rely on the assumption of complete information and have low utilization of historical trading strategy information, a capacity market trading simulation method based on prioritized experience replay multi- agent deep deterministic policy gradient (PER-MADDPG) is proposed. The action space is constructed using quantity bidding strategy and price bidding strategy, and the state space is constructed using historical transaction strategies and winning …
An Automated Generation Method For Combat Simulation Scenarios Based On Large Language Models,
2026
Army Arms University of PLA, Beijing 100072, China
An Automated Generation Method For Combat Simulation Scenarios Based On Large Language Models, Zhiming Dong, Zhongqi Hu, Haoran Dai, Jiancheng Gao
Journal of System Simulation
To address the issue of low efficiency in generating traditional army tactical combat simulation scenarios, an automated generation method based on large language models is proposed. The large language model invokes a semantic segmentation algorithm to parse and restructure the combat scenario, forming semantic modules. Utilizing a multi-agent collaborative framework based on the model contextual protocol, the large language model drives each agent to extract simulation elements from the corresponding semantic modules, constructing a knowledge graph of scenario elements. Using this knowledge graph as a retrieval medium, the method employs a dense retrieval algorithm to achieve precise matching between simulation …
Robust Identification Of Black-Box Nonlinear Ssm Using Expectation-Maximization,
2026
Control and Simulation Center, Harbin Institute of Technology, Harbin 150001, China; National Key Laboratory of Air-based Information Perception and Fusion, Luoyang 471009, China
Robust Identification Of Black-Box Nonlinear Ssm Using Expectation-Maximization, Xiaonan Li, Tao Chao, Ping Ma, Ming Yang, Yuxuan Wang
Journal of System Simulation
To address the robust identification problem of nonlinear state space models (SSM) with outliers, missing observations, and unknown state equations, this paper proposes a modeling method based on eigenfunction expansion, Gaussian-process state-space models (GP-SSM), and Student-t distribution. The proposed approach consists of: modeling the state transition function using eigenfunctions and pre-encoding the priors of basis function coefficients via GP-SSM to enhance flexibility; modeling observations as a Student-t distribution with unknown parameters to enhance robustness against outliers; proposing the enhanced particle Gibbs with ancestor sampling (EPGAS) algorithm to adapt to state estimation in scenarios with missing observations; and deriving unknown model …
Multi-Agent Cbs Path Planning Algorithm Based On Minimum Planning Margin First,
2026
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China
Multi-Agent Cbs Path Planning Algorithm Based On Minimum Planning Margin First, Longxiao Liang, Jianlin Mao, Niya Wang, Chengyuan Fang, Wenna Zhou
Journal of System Simulation
To address the problems of chain effect and insufficient solving efficiency in the conflict tree (CT) expansion of the traditional conflict-based search (CBS) framework, a minimum-margin-first CBS algorithm based on planning margin was proposed. The calculation of planning margin was introduced into the underlying A* search, and the robots with the minimum margin were prioritized in the high-level conflict resolution, to suppress the chain expansion of the CT while ensuring path optimality.Simulation experiments show that the proposed algorithm significantly reduces the amount of CT node expansion and the number of root node conflicts and effectively improves the solving efficiency, …
