Both necessary and sufficient maximum principles for optimal control of stochastic systemwith random jumps consisting of forward and backward state variables are proved.The control variableis allowed to enter both dif...Both necessary and sufficient maximum principles for optimal control of stochastic systemwith random jumps consisting of forward and backward state variables are proved.The control variableis allowed to enter both diffusion and jump coefficients.The result is applied to a mean-varianceportfolio selection mixed with a recursive utility functional optimization problem.Explicit expressionof the optimal portfolio selection strategy is obtained in the state feedback form.展开更多
The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible ...The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.展开更多
In this paper, adaptive identification and control of nonlinear dynamical systems are investigated using radial basis function networks (RBF). Firstly, a novel approach to train the RBF is introduced, which employs an...In this paper, adaptive identification and control of nonlinear dynamical systems are investigated using radial basis function networks (RBF). Firstly, a novel approach to train the RBF is introduced, which employs an adaptive fuzzy generalized learning vector quantization (AFGLVQ) technique and recursive least squares algorithm with variable forgetting factor (VRLS). The AFGLVQ adjusts the centers of the RBF while the VRLS updates the connection weights of the network. The identification algorithm has the properties of rapid convergence and persistent adaptability that make it suitable for real-time control. Secondly, on the basis of the one-step ahead RBF predictor, the control law is optimized iteratively through a numerical stable Davidon's least squares-based (SDLS) minimization approach. Four nonlinear examples are simulated to demonstrate the effectiveness of the identification and control algorithms.展开更多
Since the beginning of March 2022,the epidemic due to the Omicron variant has developed rapidly in Jilin Province.To figure out the key controlling factors and validate the model to show the success of the Zero-COVID ...Since the beginning of March 2022,the epidemic due to the Omicron variant has developed rapidly in Jilin Province.To figure out the key controlling factors and validate the model to show the success of the Zero-COVID policy in the province,we constructed a Recursive Zero-COVID Model quantifying the strength of the control measures,and defined the control reproduction number as an index for describing the intensity of interventions.Parameter estimation and sensitivity analysis were employed to estimate and validate the impact of changes in the strength of different measures on the intensity of public health preventions qualitatively and quantitatively.The recursive Zero-COVID model predicted that the dates of elimination of cases at the community level of Changchun and Jilin Cities to be on April 8 and April 17,respectively,which are consistent with the real situation.Our results showed that the strict implementation of control measures and adherence of the public are crucial for controlling the epidemic.It is also essential to strengthen the control intensity even at the final stage to avoid the rebound of the epidemic.In addition,the control reproduction number we defined in the paper is a novel index to measure the intensity of the prevention and control measures of public health.展开更多
In this paper,we study the recursive stochastic optimal control problems.The control domain does not need to be convex,and the generator of the backward stochastic differential equation can contain z.We obtain the var...In this paper,we study the recursive stochastic optimal control problems.The control domain does not need to be convex,and the generator of the backward stochastic differential equation can contain z.We obtain the variational equations for backward stochastic differential equations,and then obtain the maximum principle which solves completely Peng’s open problem.展开更多
We study mean-field type optimal stochastic control problem for systems governed by mean-field controlled forward-backward stochastic differential equations with jump processes,in which the coefficients depend on the ...We study mean-field type optimal stochastic control problem for systems governed by mean-field controlled forward-backward stochastic differential equations with jump processes,in which the coefficients depend on the marginal law of the state process through its expected value.The control variable is allowed to enter both diffusion and jump coefficients.Moreover,the cost functional is also of mean-field type.Necessary conditions for optimal control for these systems in the form of maximum principle are established by means of convex perturbation techniques.As an application,time-inconsistent mean-variance portfolio selectionmixed with a recursive utility functional optimization problem is discussed to illustrate the theoretical results.展开更多
在自适应供应链(AdaptSC)及其主要特性的分析研究基础上,运用活性系统模型(viable systems model,VSM)的核心思想,对自适应供应链的递归结构进行了构建与研究。结合具体公司情境,从整体上描述其组成部分及各部分之间的相互关系,以递归...在自适应供应链(AdaptSC)及其主要特性的分析研究基础上,运用活性系统模型(viable systems model,VSM)的核心思想,对自适应供应链的递归结构进行了构建与研究。结合具体公司情境,从整体上描述其组成部分及各部分之间的相互关系,以递归结构描述其应对突发事件的能力和自适应机理,利用结构熵模型,从信息传输效率的角度对该公司的自适应供应链递归结构进行测量与实证。研究结果表明,递归结构更有利于自适应供应链的构建与应用。自适应供应链的结构设计研究对供应链信息技术开发与应用、先进供应链的实施与管理具有非常重要的指导意义。展开更多
基金supported by the National Basic Research Program of China (973 Program) under Grant No.2007CB814904the National Natural Science Foundations of China under Grant Nos.10921101 and 10701050the Natural Science Foundation of Shandong Province under Grant Nos.JQ200801 and 2008BS01024
文摘Both necessary and sufficient maximum principles for optimal control of stochastic systemwith random jumps consisting of forward and backward state variables are proved.The control variableis allowed to enter both diffusion and jump coefficients.The result is applied to a mean-varianceportfolio selection mixed with a recursive utility functional optimization problem.Explicit expressionof the optimal portfolio selection strategy is obtained in the state feedback form.
文摘The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.
文摘In this paper, adaptive identification and control of nonlinear dynamical systems are investigated using radial basis function networks (RBF). Firstly, a novel approach to train the RBF is introduced, which employs an adaptive fuzzy generalized learning vector quantization (AFGLVQ) technique and recursive least squares algorithm with variable forgetting factor (VRLS). The AFGLVQ adjusts the centers of the RBF while the VRLS updates the connection weights of the network. The identification algorithm has the properties of rapid convergence and persistent adaptability that make it suitable for real-time control. Secondly, on the basis of the one-step ahead RBF predictor, the control law is optimized iteratively through a numerical stable Davidon's least squares-based (SDLS) minimization approach. Four nonlinear examples are simulated to demonstrate the effectiveness of the identification and control algorithms.
基金the National Natural Science Foundation of China,China(12101157,12126206)Natural Science Foundation of Jilin Province,China(20210101482JC)Natural Science Foundation of Heilongjiang Province,China(LH2021A003).
文摘Since the beginning of March 2022,the epidemic due to the Omicron variant has developed rapidly in Jilin Province.To figure out the key controlling factors and validate the model to show the success of the Zero-COVID policy in the province,we constructed a Recursive Zero-COVID Model quantifying the strength of the control measures,and defined the control reproduction number as an index for describing the intensity of interventions.Parameter estimation and sensitivity analysis were employed to estimate and validate the impact of changes in the strength of different measures on the intensity of public health preventions qualitatively and quantitatively.The recursive Zero-COVID model predicted that the dates of elimination of cases at the community level of Changchun and Jilin Cities to be on April 8 and April 17,respectively,which are consistent with the real situation.Our results showed that the strict implementation of control measures and adherence of the public are crucial for controlling the epidemic.It is also essential to strengthen the control intensity even at the final stage to avoid the rebound of the epidemic.In addition,the control reproduction number we defined in the paper is a novel index to measure the intensity of the prevention and control measures of public health.
基金Research supported by NSF(No.11671231,11201262 and 10921101)Shandong Province(No.BS2013SF020 and ZR2014AP005)Young Scholars Program of Shandong University and the 111 Project(No.B12023).
文摘In this paper,we study the recursive stochastic optimal control problems.The control domain does not need to be convex,and the generator of the backward stochastic differential equation can contain z.We obtain the variational equations for backward stochastic differential equations,and then obtain the maximum principle which solves completely Peng’s open problem.
基金The first author was partially supported by Algerian CNEPRU Project Grant B01420130137,2014-2016.
文摘We study mean-field type optimal stochastic control problem for systems governed by mean-field controlled forward-backward stochastic differential equations with jump processes,in which the coefficients depend on the marginal law of the state process through its expected value.The control variable is allowed to enter both diffusion and jump coefficients.Moreover,the cost functional is also of mean-field type.Necessary conditions for optimal control for these systems in the form of maximum principle are established by means of convex perturbation techniques.As an application,time-inconsistent mean-variance portfolio selectionmixed with a recursive utility functional optimization problem is discussed to illustrate the theoretical results.
文摘在自适应供应链(AdaptSC)及其主要特性的分析研究基础上,运用活性系统模型(viable systems model,VSM)的核心思想,对自适应供应链的递归结构进行了构建与研究。结合具体公司情境,从整体上描述其组成部分及各部分之间的相互关系,以递归结构描述其应对突发事件的能力和自适应机理,利用结构熵模型,从信息传输效率的角度对该公司的自适应供应链递归结构进行测量与实证。研究结果表明,递归结构更有利于自适应供应链的构建与应用。自适应供应链的结构设计研究对供应链信息技术开发与应用、先进供应链的实施与管理具有非常重要的指导意义。
