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Probabilistic stability and stabilization of human-machine system via hidden semi-Markov modeling approach

applied MATHEMATICS AND COMPUTATION 2025年 489卷

作者： Liu, Yang-Fan Wu, Huai-Ning Beihang Univ Sch Automat Sci & Elect Engn Sci & Technol Aircraft Control Lab Beijing 100191 Peoples R China Beihang Univ Hangzhou Int Innovat Inst Hangzhou 311115 Peoples R China

This paper investigates the probabilistic stability and stabilization issues of human-machine systems (H-MSs) through the use of hidden semi-Markov model (HS-MM) for human behavior modeling. Firstly, an HS-MM is employed to illustrate the sojourn-time-dependent HIS behavior, which considers the stochastic nature of human internal state (HIS) reasoning and the uncertainty from HIS observation. Next, by integrating HIS model, machine dynamic model, and human- machine interaction, a hidden semi-Markov jump system (HS-MJS) model is established to describe the H-MS. The initial machine state is considered to be Gaussian distributed with some given expected value and covariance matrix. By the tools of probabilistic reachable set computation and stochastic Lyapunov functional, a sufficient condition for the stochastic stability of the H-MS with some given confidence level is provided in terms of linear matrix inequalities (LMIs). Moreover, for a prescribed confidence level, an LMI-based human-assistance controller synthesis method is proposed to stabilize the H-MS with the confidence level. Finally, a driver- automation cooperative system is employed to verify the feasibility of the theoretical results.

关键词： Human behavior modeling Hidden semi-Markov model Human-machine system Probabilistic stability and stabilization

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Joint PDF shape optimization of modeling error sequences based LSTM modeling of multioutput industrial system 24

Joint PDF shape optimization of modeling error sequences bas...

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2nd international conference on Frontiers of Intelligent Manufacturing and Automation, CFIMA 2024

作者： Bai, Jin Li, Mingjie Zhao, Zhicheng Taiyuan University of Science and Technology Taiyuan China

ISBN: (纸本)9798400710681

Aiming at the problem that it is difficult to fully describe the dynamic stochastic characteristics by the traditional performance index characterizing the mean value of modeling error sequences, this paper proposes a novel modeling method for the multioutput industrial system by optimizing joint PDF (JPDF) shape of modeling error sequences. First, with the powerful learning and the approximation capabilities of deep neural networks, the LSTM neural network model is constructed to describe the dynamics of complex multioutput system. Meanwhile, the multidimensional kernel density estimation method is used to compute the JPDF shape of modeling error sequences;Second, in order to effectively reduce the randomness within the model, the JPDF shape of modeling error sequences can be gradually approximated to the desired JPDF shape by optimizing the performance index function between the JPDF shape of modeling error sequences and the desired JPDF shape;Finally, the effectiveness and advancement of the proposed method is verified based on simulation experiments of blast furnace ironmaking system. © 2024 Copyright held by the owner/author(s).

关键词： Blast furnaces

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28th international conference on Analytical and stochastic modeling Techniques and Applications, ASMTA 2024

28th International Conference on Analytical and Stochastic M...

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28th international conference on Analytical and stochastic modeling Techniques and Applications, ASMTA 2024

ISBN: (纸本)9783031707520

The proceedings contain 10 papers. The special focus in this conference is on Analytical and stochastic modeling Techniques and Applications. The topics include: Optimal Allocation of Tasks to Networked Computing Facilities;revenue Management for Parallel Services with Fully Observable Queues;Deep Reinforcement Learning for Weakly Coupled MDP’s with Continuous Actions;a Lazy Abstraction Algorithm for Markov Decision Processes: Theory and Initial Evaluation;queueing Analysis of an Ensemble Machine Learning system;analysis of Load Balancing Prioritization for Heterogeneous M/M/c/K Server Clusters in the Stationary Mean-Field Regime;An Algebraic Proof of the Relation of Markov Fluid Queues and QBD Processes;stability Condition for the Multi-server Job Queuing Model: Sensitivity Analysis.

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CONTINUOUS stochastic DYNAMICS OF GAMES WITH THREE PURE STRATEGIES SUBJECT TO INTRINSIC NOISE

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Journal of Mathematical Sciences (United States) 2025年 1-9页

作者： Rupp, Florian School of Mathematics Kutaisi International University Youth Avenue 5th Lane Kutaisi 4600 Georgia Western Caspian University 31 Istiglaliyyat Baku 1001 Azerbaijan

Typically, randomness in evolutionary games is included by equipping the discrete deterministic replicator dynamics with Moran noise processes. Here, we extend this approach to obtain, from first principles, continuous evolution equations subject to white noise excitation. The modeling of these stochastic replicator dynamics will follow the approach applied in biological systems subject to system-internal random fluctuations. Our focus of study is evolutionary games with three pure strategies as they can be found by playing rock-scissor-paper or, in nature, by the territorial dynamics of the side-blotched lizards Uta stansburiana. Simulations of the stochastic game dynamics in its phase space together with discussions of the evolutionary stability of the equilibria will round up the presentation. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Evolutionary game theory Non-linear stochastic equations stochastic replicator dynamics

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Krause Mean Processes Generated by Doubly stochastic Hyper-Matrices with Positive Influences 28th

Krause Mean Processes Generated by Doubly Stochastic Hyper-...

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28th international conference on Difference Equations and Applications, ICDEA 2023

作者： Saburov, Mansoor Saburov, Khikmat Saburov, Khajibay Hawally Kuwait Kimyo International University in Tashkent Tashkent Uzbekistan University of Tashkent for Applied Sciences Tashkent Uzbekistan

ISBN: (纸本)9783031820021

The notion of consensus through repeated averaging was first introduced by DeGroot in the context of synchronous environments. Since then, consensus has been extensively studied in a diverse range of fields, including biology, physics, and control engineering. The Krause mean process is a generalized model of opinion dynamics among many agents that represents opinions as vectors. In this paper, we investigate an opinion sharing dynamics in the multi-agent system by means of Krause mean processes which are generated by doubly stochastic hyper-matrices. This is arguably a feasible generalization of the classical models such as DeGroot’s model as well as Chatterjee-Seneta’s model from square stochastic matrices to higher-order stochastic hyper-matrices. We then demonstrate how consensus can be achieved in the multi-agent system when doubly stochastic hyper-matrices have positive influences. This is a novel generalization of the Perron-Frobenius theorem from doubly stochastic square matrices to doubly stochastic hyper-matrices with positive influences. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Multi agent systems

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Enhancing Urban Building Energy Simulations: Advanced Evaluation of stochastic Occupancy Models with Real Occupancy Data 9th

Enhancing Urban Building Energy Simulations: Advanced Evalua...

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9th international Building Physics conference

作者： Dabirian, Sanam Alamatsaz, Kayhan Eicker, Ursula Concordia Univ Montreal PQ H3H 2L9 Canada Canada Excellence Res Chair Montreal PQ Canada

ISBN: (纸本)9789819783113;9789819783090;9789819783083

The precision of energy simulations in buildings is crucial for efficiently managing and sustaining energy resources, particularly in intricate settings like university campuses. This study investigates how to enhance energy simulation models by integrating detailed occupancy data, evaluating stochastic occupancy models, and comparing the actual data of urban building archetypes. Traditional energy models, which often rely on standardized occupancy schedules, can lead to significant discrepancies between predicted and actual energy usage. This study introduces an approach incorporating electricity consumption data from campus facility management into building simulation models. This data reflects actual occupancy patterns, including peak and off-peak usage periods, transient populations, and space-specific activities, providing a more accurate simulation basis. The proposed model was applied to a group of buildings at Concordia University, Montreal, Canada. The results indicate a significant improvement in the model predictive accuracy, with the mean-variance reduced by 11%, highlighting the critical impact of accurately modeling occupancy patterns on energy consumption. This research underscores the importance of considering occupancy dynamics in building energy simulations. By aligning simulation parameters with real-world occupancy behaviors and applying them to urban building archetypes, it is possible to achieve more accurate energy conservation measures and sustainable practices. The findings demonstrate the potential for using existing infrastructure as scalable, cost-effective tools for collecting occupancy data, offering a novel, practical approach to enhancing simulation accuracy in various urban environments and promoting more sustainable, energy-efficient operations in campus settings.

关键词： Urban building energy modeling Occupancy modeling stochastic modeling

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Probabilistic modeling and Uncertainty Quantification of Harmonic Distortions in Grid-Integrated Inverters Through Bayesian Neural Networks

Probabilistic Modeling and Uncertainty Quantification of Har...

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2025 international conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Rao, Srinivasa Awasthy, Neeta Asha, V. Nijhawan, Ginni Singh, Gurmeet Albawi, Ali Annapoorna, E. Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Gl Bajaj Group of Institutions Department of Computer Science and Engineering U.P. Mathura India New Horizon College of Engineering Bangalore India Lovely Professional University Phagwara India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Department of Aimle Griet Telangana Hyderabad India

ISBN: (纸本)9798331527495

Harmonic distortion in grid connected inverters Thus, impacts on power quality and system stability are high, and more especially for systems that use renewable energy sources. This research presents a new stochastic predictive modelling approach based on Bayesian Neural Networks for forecasting of harmonic distortions with prediction uncertainty. The proposed methodology uses data from the National Renewable Energy Laboratory (NREL) database that consists of detailed grid voltage, current under various REMs. Harmonics components derived via sophisticated signal processing algorithms then yields the desired data base for training and testing. The uncertainty of grid conditions can be modelled by means of probabilities due to the utilization of BNNs for improving the reliability of predictions. The combination of stochastic modelling and harmonic analysis in this work creates a complex approach to enhancing grid stability and power quality. As applied to renewable energy challenges, the common method enhances the proposed approach as a scalable and adaptive solution for the mitigation of harmonic impacts for future power systems. © 2025 IEEE.

关键词： stochastic models

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TD3 compensated control for uncertain AUV trajectory tracking 2

TD3 compensated control for uncertain AUV trajectory trackin...

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2nd international conference on the Frontiers of Intelligent Control, Measurement, and Signal systems, FICMSS 2025

作者： Liu, Zhiqun Chen, Chaoyang Huang, Yi Yang, Dan Hunan University of Science and Technology Taoyuan Road Yuhu District Hunan Province Xiangtan City China

This paper investigates the trajectory tracking problem of autonomous underwa-ter vehicles (AUV).In order to solve the problems of underdrive,non-completeness,strong cou-pling and modeling errors with random perturbations that may be encountered by underwater autonomous vehicles,in real operations. The ideal model, i.e.,the nominal model,is firstly es-tablished based on the non-completely underdriven strongly coupled AUV dynamics,and the nominal model control rate is designed based on the backstepping method and Lyapunov *** reinforcement learning techniques are then utilized to deal with modeling errors and stochastic perturbations of the system model in real operations,and a compensation method based on the Twin Delayed Deep Deterministic policy gradient(TD3) is ***,numerical simulation is carried out,and the simulation results show that the control method proposedin this paper effectively reduces the effects of modeling errors and random perturbations,on the accurate trajectory tracking of AUV. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： stochastic control systems

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Applications of Sustainable Electric Vehicle Infrastructures Using stochastic Threshold Strategies in Green Transportation and Highway Networks 1

Applications of Sustainable Electric Vehicle Infrastructures...

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1st international conference on Sustainable Energy Technologies and Computational Intelligence, SETCOM 2025

作者： Nayi, Kuldeepkumar Ramabhai Varshney, Shreekant Srivastava, Anurag Kumar Priyadarshini, Deepti Patel, Om Pandit Deendayal Energy University School of Liberal Studies Department of Public Administration Gujarat Gandhinagar382426 India Pandit Deendayal Energy University School of Technology Department of Mathematics Gujarat Gandhinagar382426 India Swarnim Startup and Innovation University Department of Swarnim School of Computing and It Gujarat Gandhinagar382421 India Pandit Deendayal Energy University School of Technology Department of Electronics and Communication Engineering Gujarat Gandhinagar382426 India

ISBN: (纸本)9798331520540

This study presents a queueing-theoretic framework for single-server electric vehicle (EV) charging networks, utilizing threshold-based strategies to enhance EV network efficiency associated with green transportation. The approach incorporates stochastic modeling and Chapman-Kolmogorov equations to dynamically modify service rates when demand reaches predetermined thresholds, thereby minimizing waiting times and optimizing server utilization. Further, numerous system performance indicators are demonstrated to emphasize the efficiency and superior performance of EV charging infrastructures located on green highway networks. Further, numerical results illustrate the model's efficacy in addressing critical operational issues, providing a practical framework to enhance EV network performance and customer satisfaction. © 2025 IEEE.

关键词： stochastic systems

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Platform-specific code generation method for the tyche embedded operating system based on AADL models 3

Platform-specific code generation method for the tyche embed...

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3rd international conference on Algorithms, Network, and Communication Technology, ICANCT 2024

作者： Chen, Li Jia, Zhangtao An, Heng Li, Haoyu Beijing Computer Technology and Application Research Institute Beijing China

ISBN: (数字)9781510688902

ISBN: (纸本)9781510688896

The Tyche Embedded Operating system is a highly customized real-time embedded operating system, widely applied in fields such as aerospace, medical devices, and industrial automation. Renowned for its robust support for real-time tasks and efficient resource management, this system has become a core technology in embedded system development. The Architecture Analysis and Design Language (AADL), as a stringent standardized modeling language, possesses powerful expressiveness and scalability. This paper proposes a method for generating platform-specific code for the Tyche Embedded Operating system based on AADL models, which involves describing complex systems through AADL modeling and generating safety-critical software suitable for the Tyche Embedded Operating system. Firstly, the paper elaborates on the key aspects of the AADL standard and adheres to these aspects for modeling safety-critical systems. Secondly, an intermediate layer is introduced, outlining the mapping rules from the AADL common subset to the intermediate code, generating intermediate code for each component within the system architecture, and ultimately compiling it into C code applicable to the Tyche platform. Finally, a prototype tool for code generation is provided, and the effectiveness of the proposed method is validated through a case study of a temperature control system. © 2025 SPIE.

关键词： Program compilers

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