Pub Date : 2024-10-16DOI: 10.1016/j.amc.2024.129128
G.D. Rublev , A.N. Parshikov , S.A. Dyachkov
The study examines the origin of errors resulting from the approximation of the right hand sides of the Euler equations using the Godunov type contact method of smoothed particle hydrodynamics (CSPH). The analytical expression for the numerical shear viscosity in CSPH method is obtained. In our recent study the numerical viscosity was determined by comparing the numerical solution of momentum diffusion in the shear flow with theoretical one. In this study we deduce the analytical expression for the numerical viscosity which is found to be similar to numerical one, confirming the obtained results. To reduce numerical diffusion, diffusion limiters are typically applied to expressions for contact values of velocity and pressure, as well as higher-order reconstruction schemes. Based on the performed theoretical analysis, we propose a new method for correcting quantities at interparticle contacts in CSPH method, which can be easily extended to the MUSCL-type (Monotonic Upstream-centered Scheme for Conservation Laws) method. Original CSPH and MUSCL-SPH approaches and ones with aforementioned correction are compared.
{"title":"Improving approximation accuracy in Godunov-type smoothed particle hydrodynamics methods","authors":"G.D. Rublev , A.N. Parshikov , S.A. Dyachkov","doi":"10.1016/j.amc.2024.129128","DOIUrl":"10.1016/j.amc.2024.129128","url":null,"abstract":"<div><div>The study examines the origin of errors resulting from the approximation of the right hand sides of the Euler equations using the Godunov type contact method of smoothed particle hydrodynamics (CSPH). The analytical expression for the numerical shear viscosity in CSPH method is obtained. In our recent study the numerical viscosity was determined by comparing the numerical solution of momentum diffusion in the shear flow with theoretical one. In this study we deduce the analytical expression for the numerical viscosity which is found to be similar to numerical one, confirming the obtained results. To reduce numerical diffusion, diffusion limiters are typically applied to expressions for contact values of velocity and pressure, as well as higher-order reconstruction schemes. Based on the performed theoretical analysis, we propose a new method for correcting quantities at interparticle contacts in CSPH method, which can be easily extended to the MUSCL-type (Monotonic Upstream-centered Scheme for Conservation Laws) method. Original CSPH and MUSCL-SPH approaches and ones with aforementioned correction are compared.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1016/j.amc.2024.129130
Mengyu Zhou , Xingwen Liu , Qi Hu , Feng Shu
As an effective strategy for load management in smart grids, demand response establishes a bidirectional connection between the electricity supplier and users. Based on the networked evolutionary game theory, this paper studies the demand-response issue for a class of smart grids by using the semi-tensor product of matrices. The paper proceeds as follows. (i) Considering the dynamic interactions between the supplier and users, the demand response is modeled as a heterogeneous networked evolutionary game and is expressed as dynamical form by semi-tensor product. (ii) A sufficient and necessary condition is provided to verify the convergence to a fixed point of the considered system. (iii) A feedback controller is designed to ensure the system electricity consumption and price to maintain at a desired level. Finally, an example is presented to illustrate the feasibility of the proposed method.
{"title":"Analysis and control of demand response in smart grids: An evolutionary game method","authors":"Mengyu Zhou , Xingwen Liu , Qi Hu , Feng Shu","doi":"10.1016/j.amc.2024.129130","DOIUrl":"10.1016/j.amc.2024.129130","url":null,"abstract":"<div><div>As an effective strategy for load management in smart grids, demand response establishes a bidirectional connection between the electricity supplier and users. Based on the networked evolutionary game theory, this paper studies the demand-response issue for a class of smart grids by using the semi-tensor product of matrices. The paper proceeds as follows. (i) Considering the dynamic interactions between the supplier and users, the demand response is modeled as a heterogeneous networked evolutionary game and is expressed as dynamical form by semi-tensor product. (ii) A sufficient and necessary condition is provided to verify the convergence to a fixed point of the considered system. (iii) A feedback controller is designed to ensure the system electricity consumption and price to maintain at a desired level. Finally, an example is presented to illustrate the feasibility of the proposed method.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1016/j.amc.2024.129117
Ahmad Aghapour , Hamid Arian , Luis Seco
This paper presents the Deep-Time Neural Network (DTNN), an efficient and novel deep-learning approach for solving partial differential equations (PDEs). DTNN leverages the power of deep neural networks to approximate the solution for a class of quasi-linear parabolic PDEs. We demonstrate that DTNN significantly reduces the computational cost and speeds up the training process compared to other models in the literature. The results of our study indicate that DTNN architecture is promising for the fast and accurate solution of time-dependent PDEs in various scientific and engineering applications. The DTNN architecture addresses the pressing need for enhanced time considerations in the deeper layers of Artificial Neural Networks (ANNs), thereby improving convergence time for high-dimensional PDE solutions. This is achieved by integrating time into the hidden layers of the DTNN, demonstrating a marked improvement over existing ANN-based solutions regarding efficiency and speed.
{"title":"Deep-time neural networks: An efficient approach for solving high-dimensional PDEs","authors":"Ahmad Aghapour , Hamid Arian , Luis Seco","doi":"10.1016/j.amc.2024.129117","DOIUrl":"10.1016/j.amc.2024.129117","url":null,"abstract":"<div><div>This paper presents the Deep-Time Neural Network (DTNN), an efficient and novel deep-learning approach for solving partial differential equations (PDEs). DTNN leverages the power of deep neural networks to approximate the solution for a class of quasi-linear parabolic PDEs. We demonstrate that DTNN significantly reduces the computational cost and speeds up the training process compared to other models in the literature. The results of our study indicate that DTNN architecture is promising for the fast and accurate solution of time-dependent PDEs in various scientific and engineering applications. The DTNN architecture addresses the pressing need for enhanced time considerations in the deeper layers of Artificial Neural Networks (ANNs), thereby improving convergence time for high-dimensional PDE solutions. This is achieved by integrating time into the hidden layers of the DTNN, demonstrating a marked improvement over existing ANN-based solutions regarding efficiency and speed.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1016/j.amc.2024.129120
Jixiu Qiu , Yonghui Zhou
We propose a generalized continuous-time insider trading model, building upon the frameworks of Caldentey and Stacchetti (2010) and Collin-Dufresne and Fos (2016), with a correlation between the value of a risky asset following an Ornstein-Uhlenbeck-type process and the noise trading volume with volatility characterized by a general stochastic process. And a closed form of the market equilibrium is established, consisting of the insider's trading strategy and the market makers' pricing rule. It shows that at the equilibrium: (i) all of the insider's private information is released at the end of the transaction; (ii) market depth and market liquidity evolve as semi-martingales, respectively; and (iii) the equilibrium price is driven by a bridge process that solves an Ornstein-Uhlenbeck-type SDE. Numerical simulations show that as the correlation coefficient increases, the equilibrium price becomes more informative, leading to a decrease in both the trading intensity and the expected payoff for the insider.
{"title":"Insider trading at a random deadline with correlation between dynamic asset and stochastic liquidity","authors":"Jixiu Qiu , Yonghui Zhou","doi":"10.1016/j.amc.2024.129120","DOIUrl":"10.1016/j.amc.2024.129120","url":null,"abstract":"<div><div>We propose a generalized continuous-time insider trading model, building upon the frameworks of Caldentey and Stacchetti (2010) and Collin-Dufresne and Fos (2016), with a correlation between the value of a risky asset following an Ornstein-Uhlenbeck-type process and the noise trading volume with volatility characterized by a general stochastic process. And a closed form of the market equilibrium is established, consisting of the insider's trading strategy and the market makers' pricing rule. It shows that at the equilibrium: (i) all of the insider's private information is released at the end of the transaction; (ii) market depth and market liquidity evolve as semi-martingales, respectively; and (iii) the equilibrium price is driven by a bridge process that solves an Ornstein-Uhlenbeck-type SDE. Numerical simulations show that as the correlation coefficient increases, the equilibrium price becomes more informative, leading to a decrease in both the trading intensity and the expected payoff for the insider.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1016/j.amc.2024.129114
Yaolong Yu , Zhengtian Wu , Baoping Jiang , Huaicheng Yan , Yichen Lu
The minimisation of concave costs in the supply chain presents a challenging non-deterministic polynomial (NP) optimisation problem, widely applicable in industrial and management engineering. To approximate solutions to this problem, we propose a logarithmic descent direction algorithm (LDDA) that utilises the Lagrange logarithmic barrier function. As the barrier variable decreases from a high positive value to zero, the algorithm is capable of tracking the minimal track of the logarithmic barrier function, thereby obtaining top-quality solutions. The Lagrange function is utilised to handle linear equality constraints, whilst the logarithmic barrier function compels the solution towards the global or near-global optimum. Within this concave cost supply model, a logarithmic descent direction is constructed, and an iterative optimisation process for the algorithm is proposed. A corresponding Lyapunov function naturally emerges from this descent direction, thus ensuring convergence of the proposed algorithm. Numerical results demonstrate the effectiveness of the algorithm.
{"title":"A Lagrange barrier approach for the minimum concave cost supply problem via a logarithmic descent direction algorithm","authors":"Yaolong Yu , Zhengtian Wu , Baoping Jiang , Huaicheng Yan , Yichen Lu","doi":"10.1016/j.amc.2024.129114","DOIUrl":"10.1016/j.amc.2024.129114","url":null,"abstract":"<div><div>The minimisation of concave costs in the supply chain presents a challenging non-deterministic polynomial (NP) optimisation problem, widely applicable in industrial and management engineering. To approximate solutions to this problem, we propose a logarithmic descent direction algorithm (LDDA) that utilises the Lagrange logarithmic barrier function. As the barrier variable decreases from a high positive value to zero, the algorithm is capable of tracking the minimal track of the logarithmic barrier function, thereby obtaining top-quality solutions. The Lagrange function is utilised to handle linear equality constraints, whilst the logarithmic barrier function compels the solution towards the global or near-global optimum. Within this concave cost supply model, a logarithmic descent direction is constructed, and an iterative optimisation process for the algorithm is proposed. A corresponding Lyapunov function naturally emerges from this descent direction, thus ensuring convergence of the proposed algorithm. Numerical results demonstrate the effectiveness of the algorithm.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-15DOI: 10.1016/j.amc.2024.129111
Yujian Jiao , Tingting Li , Zhongqiang Zhang
In this paper, we study the Jacobi spectral collocation method for two-dimensional space-fractional Navier-Stokes equations with Laplacian and fractional Laplacian. We first derive modified fractional differentiation matrices to accommodate the singularity in two dimensions and verify the boundedness of its spectral radius. Next, we construct a fully discrete scheme for the space-fractional Navier-Stokes equations, combined with the first-order implicit-explicit Euler time-stepping scheme at the Jacobi-Gauss-Lobatto collocation points. Through some two-dimensional numerical examples, we present the influence of different parameters in the equations on numerical errors. Various numerical examples verify the effectiveness of our method and suggest the smoothness of the solution for further regularity analysis.
{"title":"Jacobi spectral collocation method of space-fractional Navier-Stokes equations","authors":"Yujian Jiao , Tingting Li , Zhongqiang Zhang","doi":"10.1016/j.amc.2024.129111","DOIUrl":"10.1016/j.amc.2024.129111","url":null,"abstract":"<div><div>In this paper, we study the Jacobi spectral collocation method for two-dimensional space-fractional Navier-Stokes equations with Laplacian and fractional Laplacian. We first derive modified fractional differentiation matrices to accommodate the singularity in two dimensions and verify the boundedness of its spectral radius. Next, we construct a fully discrete scheme for the space-fractional Navier-Stokes equations, combined with the first-order implicit-explicit Euler time-stepping scheme at the Jacobi-Gauss-Lobatto collocation points. Through some two-dimensional numerical examples, we present the influence of different parameters in the equations on numerical errors. Various numerical examples verify the effectiveness of our method and suggest the smoothness of the solution for further regularity analysis.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-15DOI: 10.1016/j.amc.2024.129125
V.T. Elayabharath , P. Sozhaeswari , N. Tatar , R. Sakthivel , T. Satheesh
With the aid of a resilient fuzzy observer, this study delves into the investigation of finite-time state and fault estimation for parabolic-type nonlinear PDE systems described by fuzzy models with faults and external disturbances. Primarily, a fuzzy-dependent observer is built to offer precise estimations of the states and faults simultaneously. Therein, the fluctuations that exhibit random character are taken into account in the observer gain, which enhances the resiliency of the configured fuzzy observer. Meanwhile, the phenomenon of randomly occurring gain fluctuations is effectively characterized by utilizing a random variable that adheres to the Bernoulli distribution. Subsequently, by employing the Lyapunov stability theory and the integral-based Wirtinger's inequality, a set of adequate criteria is obtained in the form of linear matrix inequalities to ascertain that both the state and fault estimation errors are stable in a finite-time with a gratified extended passivity performance index. In the meantime, the observer gain matrices can be obtained by relying on the developed criteria. Ultimately, the simulation results of the Fisher equation are offered to emphasize the superiority of the developed resilient fuzzy observer-based approach.
{"title":"Resilient observer-based unified state and fault estimation for nonlinear parabolic PDE systems via fuzzy approach over finite-time interval","authors":"V.T. Elayabharath , P. Sozhaeswari , N. Tatar , R. Sakthivel , T. Satheesh","doi":"10.1016/j.amc.2024.129125","DOIUrl":"10.1016/j.amc.2024.129125","url":null,"abstract":"<div><div>With the aid of a resilient fuzzy observer, this study delves into the investigation of finite-time state and fault estimation for parabolic-type nonlinear PDE systems described by fuzzy models with faults and external disturbances. Primarily, a fuzzy-dependent observer is built to offer precise estimations of the states and faults simultaneously. Therein, the fluctuations that exhibit random character are taken into account in the observer gain, which enhances the resiliency of the configured fuzzy observer. Meanwhile, the phenomenon of randomly occurring gain fluctuations is effectively characterized by utilizing a random variable that adheres to the Bernoulli distribution. Subsequently, by employing the Lyapunov stability theory and the integral-based Wirtinger's inequality, a set of adequate criteria is obtained in the form of linear matrix inequalities to ascertain that both the state and fault estimation errors are stable in a finite-time with a gratified extended passivity performance index. In the meantime, the observer gain matrices can be obtained by relying on the developed criteria. Ultimately, the simulation results of the Fisher equation are offered to emphasize the superiority of the developed resilient fuzzy observer-based approach.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-14DOI: 10.1016/j.amc.2024.129123
Hengameh Tamimi, Mohammad Bagher Ghaemi, Reza Saadati
This article explores the stochastic predator-prey model. This model offers a probabilistic framework for understanding the dynamics of interacting species. The stochastic predator-prey model is a practical tool for predicting the intricate balance of survival between predators and their prey in the face of nature's unpredictability. This study introduces a new measure of noncompactness and applies it to investigate solutions in nonlinear stochastic equations. Additionally, we present a numerical method using block pulse functions and demonstrate its convergence through the new measure of noncompactness for solving the system of stochastic integrals. Finally, the proposed method is employed to solve a numerical example.
{"title":"Coupled nonlinear stochastic integral equations in the general form of the predator-prey model","authors":"Hengameh Tamimi, Mohammad Bagher Ghaemi, Reza Saadati","doi":"10.1016/j.amc.2024.129123","DOIUrl":"10.1016/j.amc.2024.129123","url":null,"abstract":"<div><div>This article explores the stochastic predator-prey model. This model offers a probabilistic framework for understanding the dynamics of interacting species. The stochastic predator-prey model is a practical tool for predicting the intricate balance of survival between predators and their prey in the face of nature's unpredictability. This study introduces a new measure of noncompactness and applies it to investigate solutions in nonlinear stochastic equations. Additionally, we present a numerical method using block pulse functions and demonstrate its convergence through the new measure of noncompactness for solving the system of stochastic integrals. Finally, the proposed method is employed to solve a numerical example.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-14DOI: 10.1016/j.amc.2024.129124
Burhaneddin İzgi , Murat Özkaya , Nazım Kemal Üre , Matjaž Perc
In this study, we focus on examining single-agent stochastic games, especially Markov reward games represented in the form of a decision tree. We propose an alternative solution method based on the matrix norms for these games. In contrast to the existing methods such as value iteration, policy iteration, and dynamic programming, which are state-and-action-based approaches, the proposed matrix norm-based method considers the relevant stages and their actions as a whole and solves it holistically for each stage without computing the effects of each action on each state's reward individually. The new method involves a distinct transformation of the decision tree into a payoff matrix for each stage and the utilization of the matrix norm of the obtained payoff matrix. Additionally, the concept of the moving matrix is integrated into the proposed method to incorporate the impacts of all actions on the stage simultaneously, rendering the method holistic. Moreover, we present an explanatory algorithm for the implementation of the method and also provide a comprehensive solution diagram explaining the method figuratively. As a result, we offer a new and alternative perspective for solving the games with the help of the proposed method due to the simplicity of utilization of the matrix norms in addition to the existing methods. For clarification of the matrix norm-based method, we demonstrate the figurative application of the method on a benchmark Markov reward game with 2-stages and 2-actions and a comprehensive implementation of the method on a game consisting of 3-stages and 3-actions.
{"title":"A holistic matrix norm-based alternative solution method for Markov reward games","authors":"Burhaneddin İzgi , Murat Özkaya , Nazım Kemal Üre , Matjaž Perc","doi":"10.1016/j.amc.2024.129124","DOIUrl":"10.1016/j.amc.2024.129124","url":null,"abstract":"<div><div>In this study, we focus on examining single-agent stochastic games, especially Markov reward games represented in the form of a decision tree. We propose an alternative solution method based on the matrix norms for these games. In contrast to the existing methods such as value iteration, policy iteration, and dynamic programming, which are state-and-action-based approaches, the proposed matrix norm-based method considers the relevant stages and their actions as a whole and solves it holistically for each stage without computing the effects of each action on each state's reward individually. The new method involves a distinct transformation of the decision tree into a payoff matrix for each stage and the utilization of the matrix norm of the obtained payoff matrix. Additionally, the concept of the moving matrix is integrated into the proposed method to incorporate the impacts of all actions on the stage simultaneously, rendering the method holistic. Moreover, we present an explanatory algorithm for the implementation of the method and also provide a comprehensive solution diagram explaining the method figuratively. As a result, we offer a new and alternative perspective for solving the games with the help of the proposed method due to the simplicity of utilization of the matrix norms in addition to the existing methods. For clarification of the matrix norm-based method, we demonstrate the figurative application of the method on a benchmark Markov reward game with 2-stages and 2-actions and a comprehensive implementation of the method on a game consisting of 3-stages and 3-actions.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-14DOI: 10.1016/j.amc.2024.129126
Yuan-Wei Lv , Guang-Hong Yang , Georgi Marko Dimirovski
This paper investigates the distributed state estimation problem for multi-sensor networks with quantized measurements. Within the Bayesian framework, a distributed adaptive moving horizon estimation algorithm is developed. Unlike the existing methods regarding quantized errors roughly as bounded uncertainties, the posterior distributions of the errors are demanded to be derived. To overcome the difficulty of evaluating the posterior distributions for series of the states and quantized errors jointly, the variational Bayesian methodology is adopted to approximate the true distributions. Based on the fixed-point iteration method, the update rules are analytically derived, with the convergence criterion provided. Furthermore, by incorporating the average consensus algorithm into the prediction process, all sensors can achieve consensus on their estimates in a distributed manner. Finally, a numerical example of target tracking under logarithmic and uniform quantization effects is given to illustrate the validity of the proposed algorithm.
{"title":"Distributed adaptive moving horizon estimation for multi-sensor networks subject to quantization effects","authors":"Yuan-Wei Lv , Guang-Hong Yang , Georgi Marko Dimirovski","doi":"10.1016/j.amc.2024.129126","DOIUrl":"10.1016/j.amc.2024.129126","url":null,"abstract":"<div><div>This paper investigates the distributed state estimation problem for multi-sensor networks with quantized measurements. Within the Bayesian framework, a distributed adaptive moving horizon estimation algorithm is developed. Unlike the existing methods regarding quantized errors roughly as bounded uncertainties, the posterior distributions of the errors are demanded to be derived. To overcome the difficulty of evaluating the posterior distributions for series of the states and quantized errors jointly, the variational Bayesian methodology is adopted to approximate the true distributions. Based on the fixed-point iteration method, the update rules are analytically derived, with the convergence criterion provided. Furthermore, by incorporating the average consensus algorithm into the prediction process, all sensors can achieve consensus on their estimates in a distributed manner. Finally, a numerical example of target tracking under logarithmic and uniform quantization effects is given to illustrate the validity of the proposed algorithm.</div></div>","PeriodicalId":55496,"journal":{"name":"Applied Mathematics and Computation","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142432224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号