A self-adaptive control method is proposed based on an artificial neural network(ANN)with accelerated evolutionary programming(AEP)algorithm.The neural network is used to model the uncertainty process,from which the t...A self-adaptive control method is proposed based on an artificial neural network(ANN)with accelerated evolutionary programming(AEP)algorithm.The neural network is used to model the uncertainty process,from which the teacher signals are produced online to regulate the parameters of the controller.The accelerated evolutionary programming is used to train the neural network.The experiment results show that the method can obviously improve the dynamic performance of uncertainty systems.展开更多
Objective:To explore the impact of systematic stepwise rehabilitation nursing intervention on the prognosis and disease uncertainty of patients with hypertensive intracerebral hemorrhage,and to provide feasible strate...Objective:To explore the impact of systematic stepwise rehabilitation nursing intervention on the prognosis and disease uncertainty of patients with hypertensive intracerebral hemorrhage,and to provide feasible strategies for clinical nursing.Methods:Eighty patients with hypertensive intracerebral hemorrhage admitted to our hospital from January 2023 to June 2025 were selected and randomly divided into an observation group(n=40,receiving systematic stepwise rehabilitation nursing)and a control group(n=40,receiving conventional nursing).The intervention effects were analyzed by comparing changes in the National Institutes of Health Stroke Scale(NIHSS)scores for neurological recovery,Short Form 36 Health Survey(SF-36)scores for quality of life,Exercise of Self-Care Agency Scale(ESCA)scores for self-management ability,compliance,and the Mishel Uncertainty in Illness Scale(MUIS)scores between the two groups.Results:All scores in the observation group were significantly better than those in the control group after the intervention(p<0.05).Specifically,the NIHSS scores decreased more significantly,the total SF-36 scores increased,the ESCA scores increased significantly,while the MUIS scores decreased significantly,and compliance improved markedly,indicating a reduction in disease uncertainty among patients.Conclusion:Systematic stepwise rehabilitation nursing intervention can significantly improve neurological recovery,quality of life,self-management ability,and compliance in patients with hypertensive intracerebral hemorrhage,while effectively reducing disease uncertainty.It is worthy of clinical promotion and application.展开更多
For mixed-integer programming(MIP)problems in new power systems with uncertainties,existing studies tend to address uncertainty modeling or MIP solution methods in isolation.They overlook core bottlenecks arising from...For mixed-integer programming(MIP)problems in new power systems with uncertainties,existing studies tend to address uncertainty modeling or MIP solution methods in isolation.They overlook core bottlenecks arising from their coupling,such as variable dimension explosion,disrupted constraint separability,and conflicts in solution logic.To address this gap,this paper focuses on the coupling effects between the two and systematically conducts three aspects of work:first,the paper summarizes the uncertainty optimization methods suitable for addressing uncertainty-related issues in power systems,along with their respective advantages and disadvantages.It also clarifies the specific forms and operational mechanisms through which these uncertainty optimization methods are integrated into MIP models.Meanwhile,based on the application scenarios of new power systems,the paper delineates the applicable boundaries of different optimization methods;second,the paper organizes three categories of solution methods,which are exact solution methods,decomposition-based methods,and meta-heuristic algorithms.It focuses on analyzing the improvement paths of various solution methods for resolving coupling bottlenecks,as well as their applicability in different types of power system optimization problems;finally,providing a summary and presenting an outlook on future directions:artificial intelligence-enabled optimization,development of dedicated solvers for extreme scenarios,and dynamic modeling of multi-source uncertainties.This study aims to help researchers in the field of new power systems quickly grasp uncertainty optimization methods and core solution methods,bridge existing research gaps,and promote the development of this field.展开更多
This paper proposed a new systematic approach-functional evidential reasoning model(FERM) for exploring hazardous chemical operational accidents under uncertainty. First, FERM was introduced to identify various causal...This paper proposed a new systematic approach-functional evidential reasoning model(FERM) for exploring hazardous chemical operational accidents under uncertainty. First, FERM was introduced to identify various causal factors and their performance changes in hazardous chemical operational accidents, along with determining the functional failure link relationships. Subsequently, FERM was employed to elucidate both qualitative and quantitative operational accident information within a unified framework, which could be regarded as the input of information fusion to obtain the fuzzy belief distribution of each cause factor. Finally, the derived risk values of the causal factors were ranked while constructing multi-level accident causation chains to unveil the weak links in system functionality and the primary roots of operational accidents. Using the specific case of the “1·15” major explosion and fire accident at Liaoning Panjin Haoye Chemical Co., Ltd., seven causal factors and their corresponding performance changes were identified. Additionally, five accident causation chains were uncovered based on the fuzzy joint distribution of the functional assessment level(FAL) and reliability distribution(RD),revealing an overall increase in risk along the accident evolution path. The research findings demonstrated that FERM enabled the effective characterization, rational quantification and accurate analysis of the inherent uncertainties in hazardous chemical operational accident risks from a systemic perspective.展开更多
In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that globa...In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that global state asymptotic regulation can be ensured by introducing a single dynamic gain;furthermore,global asymptotic stabilization can be achieved by choosing a sufficiently large static scaling gain when the upper bounds of all system parameters are known.Especially,the output coefficient is allowed to be non-differentiable with unknown upper bound.This paper proposes a generalized Lyapunov matrix inequality based dynamic-gain scaling method,which significantly simplifies the design computational complexity by comparing with the classic backstepping method.展开更多
To improve design accuracy and reliability of structures,this study solves the uncertain natural frequencies with consideration for geometric nonlinearity and structural uncertainty.Frequencies of the laminated plate ...To improve design accuracy and reliability of structures,this study solves the uncertain natural frequencies with consideration for geometric nonlinearity and structural uncertainty.Frequencies of the laminated plate with all four edges clamped(CCCC)are derived based on Navier's method and Galerkin's method.The novelty of the current work is that the number of unknowns in the displacement field model of a CCCC plate with free midsurface(CCCC-2 plate)is only three compared with four or five in cases of other exposed methods.The present analytical method is proved to be accurate and reliable by comparing linear natural frequencies and nonlinear natural frequencies with other models available in the open literature.Furthermore,a novel method for analyzing effects of mean values and tolerance zones of uncertain structural parameters on random frequencies is proposed based on a self-developed Multiscale Feature Extraction and Fusion Network(MFEFN)system.Compared with a direct Monte Carlo Simulation(MCS),the MFEFNbased procedure significantly reduces the calculation burden with a guarantee of accuracy.Our research provides a method to calculate nonlinear natural frequencies under two boundary conditions and presentes a surrogate model to predict frequencies for accuracy analysis and optimization design.展开更多
Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal ene...Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal energy source for future deep space exploration.A whole system model of the space nuclear reactor consisting of the reactor neutron kinetics,reactivity control,reactor heat transfer,heat exchanger,and thermoelectric converter was developed.In addition,an electrical power control system was designed based on the developed dynamic model.The GRS method was used to quantitatively calculate the uncertainty of coupling parameters of the neutronics,thermal-hydraulics,and control system for the space reactor.The Spearman correlation coefficient was applied in the sensitivity analysis of system input parameters to output parameters.The calculation results showed that the uncertainty of the output parameters caused by coupling parameters had the most considerable variation,with a relative standard deviation<2.01%.Effective delayed neutron fraction was most sensitive to electrical power.To obtain optimal control performance,the non-dominated sorting genetic algorithm method was employed to optimize the controller parameters based on the uncertainty quantification calculation.Two typical transient simulations were conducted to test the adaptive ability of the optimized controller in the uncertainty dynamic system,including 100%full power(FP)to 90%FP step load reduction transient and 5%FP/min linear variable load transient.The results showed that,considering the influence of system uncertainty,the optimized controller could improve the response speed and load following accuracy of electrical power control,in which the effectiveness and superiority have been verified.展开更多
Also known as imaging spectroscopy,hyperspectral remote sensing is becoming a key technology for ecosystem and natural resource management sustainability.Hyperspectral observations can be used to measure tens to hundr...Also known as imaging spectroscopy,hyperspectral remote sensing is becoming a key technology for ecosystem and natural resource management sustainability.Hyperspectral observations can be used to measure tens to hundreds of narrow bands of reflected radiation to resolve diagnostic absorption bands and spectral shape variations associated with vegetation pigments,water status of the canopy,biochemical composition,mineralogies,and organic matter of the soil,and water quality constituents of aquatic water.These abilities allow one to make a transition between the descriptive mapping and the functional monitoring,the anticipation of stress and disturbance early,and the more accurate attribution of environmental change.This summary encompasses improvements on the entire sensor-to-product pipeline,including field and UAV(Unmanned Aerial Vehicle)system platform developments,airborne campaign and spaceborne mission developments,calibration and analysis-ready preprocessing improvements,empirical learning methodology improvements,radiative transfer-based inversion method,spectral unmixing,deep learning,and hybrid physics-machine learning.We underline the increased importance of the combination of data with LiDAR(Light Detection and Ranging),SAR(Synthetic Aperture Radar),and thermal features aimed at decreasing the level of ambiguity and enhancing operational resilience.Applications based on decision are evaluated in terms of biodiversity and habitat evaluation,vegetation functionality and restoration,stress and disturbance,sustainable agricultural production,inland water quality and coastal water quality,land degradation and soil status,and environmental impact assessment.Inhibiting factors to operational adoption have always been perceived to be domain shift by region,season,and sensor,ground truth and validation,mixed pixels and scale mismatch,preprocessing sensitivities,and desirable uncertainty quantification and product output that is interpretable.We conclude with the scalability,sustainability,service priorities,such as harmonization standards,representative benchmarking,uncertainty-aware delivery,and co-design of stakeholders.展开更多
Correction to:Nuclear Science and Techniques(2025)36:111 https://doi.org/10.1007/s41365-025-01681-9.In the sentence beginning‘The weights of the parameters used for the…’in this article,the text‘RCSs’should have ...Correction to:Nuclear Science and Techniques(2025)36:111 https://doi.org/10.1007/s41365-025-01681-9.In the sentence beginning‘The weights of the parameters used for the…’in this article,the text‘RCSs’should have read‘SCRs’.In Table 7 of this article,the column header ρ_fuel was incorrect and should have read CPv_fuel.For completeness and transparency,the old incorrect version and the corrected version of Table 7 are displayed below.展开更多
In the construction and maintenance for large space equipment,it is essential to ensure the control accuracy and improve the dexterity of the space manipulator.In this paper,a FiniteTime Convergence Kinematic Control(...In the construction and maintenance for large space equipment,it is essential to ensure the control accuracy and improve the dexterity of the space manipulator.In this paper,a FiniteTime Convergence Kinematic Control(FTCKC)added with Acceleration Level Dexterity Optimization(ALDO)scheme is proposed to solve the kinematic uncertainty and dexterity optimization problems of redundant space manipulators.Concretely,distinguishing from the asymptotic convergence property of traditional adaptive Jacobian methods,the FTCKC scheme is adopted to construct the equality constraint to address the model uncertainty problem,and its error can converge within a finite time.Subsequently,the dexterity index is reconstructed at acceleration level by a multi-level target handling method.Then,the equality constraint,optimization task,and limit constraints are reformulated as a quadratic programming problem.Moreover,a Recurrent Neural Network(RNN)is engineered for the constructed FTCKC-ALDO scheme.Finally,the superiority of the FTCKC-ALDO-RNN scheme is verified by experiments.展开更多
The increasing demand for artillery firepower,coupled with the growing size of gun barrels,imposes significant challenges on servo system performance.To address these challenges while ensuring fast and stable response...The increasing demand for artillery firepower,coupled with the growing size of gun barrels,imposes significant challenges on servo system performance.To address these challenges while ensuring fast and stable response,this paper proposes an adaptive robust controller based on an asymmetric barrier Lyapunov function(ABLF).The controller design incorporates both load and driver states through a backstepping synthesis.The overshoot and lag of barrel position errors are constrained within asymmetric boundaries,accounting for complex rotational uncertainties via an adaptive law and linear extended state observers(LESO).Simulations and experiments under typical artillery operating conditions validate the effectiveness and dynamic tracking performance of the proposed control strategy in comparison with other methods.展开更多
Aimed at the problem of stochastic routings for reprocessing operations and highly variable processing times,an open queuing network is utilized to model a typical reprocessing system.In the model,each server is subje...Aimed at the problem of stochastic routings for reprocessing operations and highly variable processing times,an open queuing network is utilized to model a typical reprocessing system.In the model,each server is subject to breakdown and has a finite buffer capacity,while repair times,breakdown times and service time follow an exponential distribution.Based on the decomposition principle and the expansion methodology,an approximation analytical algorithm is proposed to calculate the mean reprocessing time,the throughput of each server and other parameters of the processing system.Then an approach to determining the quality of disassembled parts is suggested,on the basis of which the effect of parts quality on the performance of the reprocessing system is investigated.Numerical examples show that there is a negative correlation between quality of parts and their mean reprocessing time.Furthermore,marginal reprocessing time of the parts decrease with the drop in their quality.展开更多
This paper considers a class of uncertainties with the polynomial function form of perturbation parameters, which is analogous to a fact that part information is known for some uncertainties. A sufficient condition of...This paper considers a class of uncertainties with the polynomial function form of perturbation parameters, which is analogous to a fact that part information is known for some uncertainties. A sufficient condition of robust stability is presented, and a method is also provided to estimate the stability bound for plants with the class of uncertainties. In the case of interval plants, this condition reduces to an existing result, which would show indirectly the condition is not too conservative. Methods are ...展开更多
This paper, at the first time, considers the problem of decentralized variable structure control of complex giant singular uncertainty systems by using the property of diagonally dominant matrix and Frobenius-Person t...This paper, at the first time, considers the problem of decentralized variable structure control of complex giant singular uncertainty systems by using the property of diagonally dominant matrix and Frobenius-Person theorem. The splendid selection of switching manifold for each subsystem makes the design relatively straightforward and can be easily realized. An illustrate example is given.展开更多
The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex s...The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects：uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.展开更多
To comprehensively assess fi＇actionated spacecraft, an assessment tool is developed based on lifecycle simulation under uncertainty driven by modular evolutionary stochastic models. First, fractionated spacecraft nom...To comprehensively assess fi＇actionated spacecraft, an assessment tool is developed based on lifecycle simulation under uncertainty driven by modular evolutionary stochastic models. First, fractionated spacecraft nomenclature and architecture are clarified, and assessment criteria are analyzed. The mean and standard deviation of risk adjusted lifecycle cost and net present value （NPV） are defined as assessment metrics. Second, fractionated spacecraft sizing models are briefly described, followed by detailed discussion on risk adjusted lifecycle cost and NPV models. Third, uncertainty sources over fractionated spacecraft life- cycle are analyzed and modeled with probability theory. Then the chronological lifecycle simulation process is expounded, and simulation modules are developed with object oriented methodology to build up the assessment tool. The preceding uncertainty models are integrated in these simulation modules, hence the random object status can be simulated and evolve with lifecycle timeline. A case study to investigate the fractionated spacecraft for a hypothetical earth observation mission is carried out with the proposed assessment tool, and the results show that fractionation degree and launch manifest have great influence on cost and NPV, and generally fractionated spacecraft is more advanced than its monolithic counterpart under uncertainty effect. Finally, some conclusions are given and future research topics are highlighted.展开更多
To solve the rapid transient control problem of Flight Environment Simulation System(FESS) of Altitude Ground Test Facilities(AGTF) with large heat transfer uncertainty and disturbance, a new adaptive control structur...To solve the rapid transient control problem of Flight Environment Simulation System(FESS) of Altitude Ground Test Facilities(AGTF) with large heat transfer uncertainty and disturbance, a new adaptive control structure of modified robust optimal adaptive control is presented.The mathematic modeling of FESS is given and the influence of heat transfer is analyzed through energy view. To consider the influence of heat transfer in controller design, we introduce a matched uncertainty that represents heat transfer influence in the linearized system of FESS. Based on this linear system, we deduce the design of modified robust optimal adaptive control law in a general way. Meanwhile, the robust stability of the modified robust optimal adaptive control law is proved through using Lyapunov stability theory. Then, a typical aero-engine test condition with Mach Dash and Zoom-Climb is used to verify the effectiveness of the devised adaptive controller. The simulation results show that the designed controller has servo tracking and disturbance rejection performance under heat transfer uncertainty and disturbance;the relative steady-state and dynamic errors of pressure and temperature are both smaller than 1% and 0.2% respectively. Furthermore,the influence of the modification parameter c is analyzed through simulation. Finally, comparing with the standard ideal model reference adaptive controller, the modified robust optimal adaptive controller obviously provides better control performance than the ideal model reference adaptive controller does.展开更多
The robust stability and robust stabilization problems for discrete singular systems with interval time-varying delay and linear fractional uncertainty are discussed. A new delay-dependent criterion is established for...The robust stability and robust stabilization problems for discrete singular systems with interval time-varying delay and linear fractional uncertainty are discussed. A new delay-dependent criterion is established for the nominal discrete singular delay systems to be regular, causal and stable by employing the linear matrix inequality （LMI） approach. It is shown that the newly proposed criterion can provide less conservative results than some existing ones. Then, with this criterion, the problems of robust stability and robust stabilization for uncertain discrete singular delay systems are solved, and the delay-dependent LMI conditions are obtained. Finally, numerical examples are given to illustrate the effectiveness of the proposed approach.展开更多
This paper investigates the possible sources of errors associated with tropical cyclone(TC) tracks forecasted using the Global/Regional Assimilation and Prediction System(GRAPES). In Part I, it is shown that the model...This paper investigates the possible sources of errors associated with tropical cyclone(TC) tracks forecasted using the Global/Regional Assimilation and Prediction System(GRAPES). In Part I, it is shown that the model error of GRAPES may be the main cause of poor forecasts of landfalling TCs. Thus, a further examination of the model error is the focus of Part II.Considering model error as a type of forcing, the model error can be represented by the combination of good forecasts and bad forecasts. Results show that there are systematic model errors. The model error of the geopotential height component has periodic features, with a period of 24 h and a global pattern of wavenumber 2 from west to east located between 60?S and 60?N. This periodic model error presents similar features as the atmospheric semidiurnal tide, which reflect signals from tropical diabatic heating, indicating that the parameter errors related to the tropical diabatic heating may be the source of the periodic model error. The above model errors are subtracted from the forecast equation and a series of new forecasts are made. The average forecasting capability using the rectified model is improved compared to simply improving the initial conditions of the original GRAPES model. This confirms the strong impact of the periodic model error on landfalling TC track forecasts. Besides, if the model error used to rectify the model is obtained from an examination of additional TCs, the forecasting capabilities of the corresponding rectified model will be improved.展开更多
Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employe...Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employed to identify the primary uncertainty and the mathematic model of the system was turned into an equivalent linear model with terms of secondary uncertainty.At the same time,gain adaptive sliding mode variable structure control(GASMVSC) was employed to synthesize the control effort.The results show that the unrealization problem caused by some system's immeasurable state variables in traditional fuzzy neural networks(TFNN) taking all state variables as its inputs is overcome.On the other hand,the identification by the ADRFNNs online with high accuracy and the adaptive function of the correction term's gain in the GASMVSC make the system possess strong robustness and improved steady accuracy,and the chattering phenomenon of the control effort is also suppressed effectively.展开更多
基金Key Equipment Project of China Petroleum & Chemical Corporation(SINOPEC)(No.J W05008)
文摘A self-adaptive control method is proposed based on an artificial neural network(ANN)with accelerated evolutionary programming(AEP)algorithm.The neural network is used to model the uncertainty process,from which the teacher signals are produced online to regulate the parameters of the controller.The accelerated evolutionary programming is used to train the neural network.The experiment results show that the method can obviously improve the dynamic performance of uncertainty systems.
文摘Objective:To explore the impact of systematic stepwise rehabilitation nursing intervention on the prognosis and disease uncertainty of patients with hypertensive intracerebral hemorrhage,and to provide feasible strategies for clinical nursing.Methods:Eighty patients with hypertensive intracerebral hemorrhage admitted to our hospital from January 2023 to June 2025 were selected and randomly divided into an observation group(n=40,receiving systematic stepwise rehabilitation nursing)and a control group(n=40,receiving conventional nursing).The intervention effects were analyzed by comparing changes in the National Institutes of Health Stroke Scale(NIHSS)scores for neurological recovery,Short Form 36 Health Survey(SF-36)scores for quality of life,Exercise of Self-Care Agency Scale(ESCA)scores for self-management ability,compliance,and the Mishel Uncertainty in Illness Scale(MUIS)scores between the two groups.Results:All scores in the observation group were significantly better than those in the control group after the intervention(p<0.05).Specifically,the NIHSS scores decreased more significantly,the total SF-36 scores increased,the ESCA scores increased significantly,while the MUIS scores decreased significantly,and compliance improved markedly,indicating a reduction in disease uncertainty among patients.Conclusion:Systematic stepwise rehabilitation nursing intervention can significantly improve neurological recovery,quality of life,self-management ability,and compliance in patients with hypertensive intracerebral hemorrhage,while effectively reducing disease uncertainty.It is worthy of clinical promotion and application.
基金supported by National Key R&D Program of China under Grant 2022YFB2403500。
文摘For mixed-integer programming(MIP)problems in new power systems with uncertainties,existing studies tend to address uncertainty modeling or MIP solution methods in isolation.They overlook core bottlenecks arising from their coupling,such as variable dimension explosion,disrupted constraint separability,and conflicts in solution logic.To address this gap,this paper focuses on the coupling effects between the two and systematically conducts three aspects of work:first,the paper summarizes the uncertainty optimization methods suitable for addressing uncertainty-related issues in power systems,along with their respective advantages and disadvantages.It also clarifies the specific forms and operational mechanisms through which these uncertainty optimization methods are integrated into MIP models.Meanwhile,based on the application scenarios of new power systems,the paper delineates the applicable boundaries of different optimization methods;second,the paper organizes three categories of solution methods,which are exact solution methods,decomposition-based methods,and meta-heuristic algorithms.It focuses on analyzing the improvement paths of various solution methods for resolving coupling bottlenecks,as well as their applicability in different types of power system optimization problems;finally,providing a summary and presenting an outlook on future directions:artificial intelligence-enabled optimization,development of dedicated solvers for extreme scenarios,and dynamic modeling of multi-source uncertainties.This study aims to help researchers in the field of new power systems quickly grasp uncertainty optimization methods and core solution methods,bridge existing research gaps,and promote the development of this field.
基金supported by the National Key Research&Development Program of China(2021YFB3301100)the National Natural Science Foundation of China(52004014)the Fundamental Research Funds for the Central Universities(ZY2406).
文摘This paper proposed a new systematic approach-functional evidential reasoning model(FERM) for exploring hazardous chemical operational accidents under uncertainty. First, FERM was introduced to identify various causal factors and their performance changes in hazardous chemical operational accidents, along with determining the functional failure link relationships. Subsequently, FERM was employed to elucidate both qualitative and quantitative operational accident information within a unified framework, which could be regarded as the input of information fusion to obtain the fuzzy belief distribution of each cause factor. Finally, the derived risk values of the causal factors were ranked while constructing multi-level accident causation chains to unveil the weak links in system functionality and the primary roots of operational accidents. Using the specific case of the “1·15” major explosion and fire accident at Liaoning Panjin Haoye Chemical Co., Ltd., seven causal factors and their corresponding performance changes were identified. Additionally, five accident causation chains were uncovered based on the fuzzy joint distribution of the functional assessment level(FAL) and reliability distribution(RD),revealing an overall increase in risk along the accident evolution path. The research findings demonstrated that FERM enabled the effective characterization, rational quantification and accurate analysis of the inherent uncertainties in hazardous chemical operational accident risks from a systemic perspective.
基金supported by the Zhejiang Provincial Natural Science Foundation(LY24F030011,LY23F030005)the National Natural Science Foundation of China(62373131).
文摘In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that global state asymptotic regulation can be ensured by introducing a single dynamic gain;furthermore,global asymptotic stabilization can be achieved by choosing a sufficiently large static scaling gain when the upper bounds of all system parameters are known.Especially,the output coefficient is allowed to be non-differentiable with unknown upper bound.This paper proposes a generalized Lyapunov matrix inequality based dynamic-gain scaling method,which significantly simplifies the design computational complexity by comparing with the classic backstepping method.
基金the research project funded by the Fundamental Research Funds for the Central Universities(No.HIT.OCEP.2024038)the National Natural Science Foundation of China(No.52372351)the State Key Laboratory of Micro-Spacecraft Rapid Design and Intelligent Cluster,China(No.MS02240107)。
文摘To improve design accuracy and reliability of structures,this study solves the uncertain natural frequencies with consideration for geometric nonlinearity and structural uncertainty.Frequencies of the laminated plate with all four edges clamped(CCCC)are derived based on Navier's method and Galerkin's method.The novelty of the current work is that the number of unknowns in the displacement field model of a CCCC plate with free midsurface(CCCC-2 plate)is only three compared with four or five in cases of other exposed methods.The present analytical method is proved to be accurate and reliable by comparing linear natural frequencies and nonlinear natural frequencies with other models available in the open literature.Furthermore,a novel method for analyzing effects of mean values and tolerance zones of uncertain structural parameters on random frequencies is proposed based on a self-developed Multiscale Feature Extraction and Fusion Network(MFEFN)system.Compared with a direct Monte Carlo Simulation(MCS),the MFEFNbased procedure significantly reduces the calculation burden with a guarantee of accuracy.Our research provides a method to calculate nonlinear natural frequencies under two boundary conditions and presentes a surrogate model to predict frequencies for accuracy analysis and optimization design.
基金supported by the National Natural Science Foundation of China(12305185)Natural Science Foundation of Hunan Province,China(No.2023JJ50122)+1 种基金International Cooperative Research Project of the Ministry of Education,China(No.HZKY20220355)Scientific Research Foundation of the Education Department of Hunan Province,China(No.22A0307).
文摘Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal energy source for future deep space exploration.A whole system model of the space nuclear reactor consisting of the reactor neutron kinetics,reactivity control,reactor heat transfer,heat exchanger,and thermoelectric converter was developed.In addition,an electrical power control system was designed based on the developed dynamic model.The GRS method was used to quantitatively calculate the uncertainty of coupling parameters of the neutronics,thermal-hydraulics,and control system for the space reactor.The Spearman correlation coefficient was applied in the sensitivity analysis of system input parameters to output parameters.The calculation results showed that the uncertainty of the output parameters caused by coupling parameters had the most considerable variation,with a relative standard deviation<2.01%.Effective delayed neutron fraction was most sensitive to electrical power.To obtain optimal control performance,the non-dominated sorting genetic algorithm method was employed to optimize the controller parameters based on the uncertainty quantification calculation.Two typical transient simulations were conducted to test the adaptive ability of the optimized controller in the uncertainty dynamic system,including 100%full power(FP)to 90%FP step load reduction transient and 5%FP/min linear variable load transient.The results showed that,considering the influence of system uncertainty,the optimized controller could improve the response speed and load following accuracy of electrical power control,in which the effectiveness and superiority have been verified.
文摘Also known as imaging spectroscopy,hyperspectral remote sensing is becoming a key technology for ecosystem and natural resource management sustainability.Hyperspectral observations can be used to measure tens to hundreds of narrow bands of reflected radiation to resolve diagnostic absorption bands and spectral shape variations associated with vegetation pigments,water status of the canopy,biochemical composition,mineralogies,and organic matter of the soil,and water quality constituents of aquatic water.These abilities allow one to make a transition between the descriptive mapping and the functional monitoring,the anticipation of stress and disturbance early,and the more accurate attribution of environmental change.This summary encompasses improvements on the entire sensor-to-product pipeline,including field and UAV(Unmanned Aerial Vehicle)system platform developments,airborne campaign and spaceborne mission developments,calibration and analysis-ready preprocessing improvements,empirical learning methodology improvements,radiative transfer-based inversion method,spectral unmixing,deep learning,and hybrid physics-machine learning.We underline the increased importance of the combination of data with LiDAR(Light Detection and Ranging),SAR(Synthetic Aperture Radar),and thermal features aimed at decreasing the level of ambiguity and enhancing operational resilience.Applications based on decision are evaluated in terms of biodiversity and habitat evaluation,vegetation functionality and restoration,stress and disturbance,sustainable agricultural production,inland water quality and coastal water quality,land degradation and soil status,and environmental impact assessment.Inhibiting factors to operational adoption have always been perceived to be domain shift by region,season,and sensor,ground truth and validation,mixed pixels and scale mismatch,preprocessing sensitivities,and desirable uncertainty quantification and product output that is interpretable.We conclude with the scalability,sustainability,service priorities,such as harmonization standards,representative benchmarking,uncertainty-aware delivery,and co-design of stakeholders.
文摘Correction to:Nuclear Science and Techniques(2025)36:111 https://doi.org/10.1007/s41365-025-01681-9.In the sentence beginning‘The weights of the parameters used for the…’in this article,the text‘RCSs’should have read‘SCRs’.In Table 7 of this article,the column header ρ_fuel was incorrect and should have read CPv_fuel.For completeness and transparency,the old incorrect version and the corrected version of Table 7 are displayed below.
基金supported by the National Natural Science Foundation of China(Nos.92148203 and T2388101)。
文摘In the construction and maintenance for large space equipment,it is essential to ensure the control accuracy and improve the dexterity of the space manipulator.In this paper,a FiniteTime Convergence Kinematic Control(FTCKC)added with Acceleration Level Dexterity Optimization(ALDO)scheme is proposed to solve the kinematic uncertainty and dexterity optimization problems of redundant space manipulators.Concretely,distinguishing from the asymptotic convergence property of traditional adaptive Jacobian methods,the FTCKC scheme is adopted to construct the equality constraint to address the model uncertainty problem,and its error can converge within a finite time.Subsequently,the dexterity index is reconstructed at acceleration level by a multi-level target handling method.Then,the equality constraint,optimization task,and limit constraints are reformulated as a quadratic programming problem.Moreover,a Recurrent Neural Network(RNN)is engineered for the constructed FTCKC-ALDO scheme.Finally,the superiority of the FTCKC-ALDO-RNN scheme is verified by experiments.
文摘The increasing demand for artillery firepower,coupled with the growing size of gun barrels,imposes significant challenges on servo system performance.To address these challenges while ensuring fast and stable response,this paper proposes an adaptive robust controller based on an asymmetric barrier Lyapunov function(ABLF).The controller design incorporates both load and driver states through a backstepping synthesis.The overshoot and lag of barrel position errors are constrained within asymmetric boundaries,accounting for complex rotational uncertainties via an adaptive law and linear extended state observers(LESO).Simulations and experiments under typical artillery operating conditions validate the effectiveness and dynamic tracking performance of the proposed control strategy in comparison with other methods.
文摘Aimed at the problem of stochastic routings for reprocessing operations and highly variable processing times,an open queuing network is utilized to model a typical reprocessing system.In the model,each server is subject to breakdown and has a finite buffer capacity,while repair times,breakdown times and service time follow an exponential distribution.Based on the decomposition principle and the expansion methodology,an approximation analytical algorithm is proposed to calculate the mean reprocessing time,the throughput of each server and other parameters of the processing system.Then an approach to determining the quality of disassembled parts is suggested,on the basis of which the effect of parts quality on the performance of the reprocessing system is investigated.Numerical examples show that there is a negative correlation between quality of parts and their mean reprocessing time.Furthermore,marginal reprocessing time of the parts decrease with the drop in their quality.
基金National Key Basic Research Special Fund (G19980 2 0 3 0 2 ) Shanxi Provincial Science Foundation(2 0 0 2 10 45 )
文摘This paper considers a class of uncertainties with the polynomial function form of perturbation parameters, which is analogous to a fact that part information is known for some uncertainties. A sufficient condition of robust stability is presented, and a method is also provided to estimate the stability bound for plants with the class of uncertainties. In the case of interval plants, this condition reduces to an existing result, which would show indirectly the condition is not too conservative. Methods are ...
文摘This paper, at the first time, considers the problem of decentralized variable structure control of complex giant singular uncertainty systems by using the property of diagonally dominant matrix and Frobenius-Person theorem. The splendid selection of switching manifold for each subsystem makes the design relatively straightforward and can be easily realized. An illustrate example is given.
基金National Key Basic Research Program of China,No.2010CB428403National Grand Science and Technology Special Project of Water Pollution Control and Improvement,No.2009ZX07210-006
文摘The regional hydrological system is extremely complex because it is affected not only by physical factors but also by human dimensions.And the hydrological models play a very important role in simulating the complex system.However,there have not been effective methods for the model reliability and uncertainty analysis due to its complexity and difficulty.The uncertainties in hydrological modeling come from four important aspects：uncertainties in input data and parameters,uncertainties in model structure,uncertainties in analysis method and the initial and boundary conditions.This paper systematically reviewed the recent advances in the study of the uncertainty analysis approaches in the large-scale complex hydrological model on the basis of uncertainty sources.Also,the shortcomings and insufficiencies in the uncertainty analysis for complex hydrological models are pointed out.And then a new uncertainty quantification platform PSUADE and its uncertainty quantification methods were introduced,which will be a powerful tool and platform for uncertainty analysis of large-scale complex hydrological models.Finally,some future perspectives on uncertainty quantification are put forward.
基金Foundation items： National Natural Science Foundation of China （50975280, 61004094） Program for New Century Excellent Talents in University （NCET-08-0149）+1 种基金 Fund of Innovation by Graduate School of National University of Defense Technology （B090102） Hunan Provincial Innovation Foundation for Postgraduate, China.
文摘To comprehensively assess fi＇actionated spacecraft, an assessment tool is developed based on lifecycle simulation under uncertainty driven by modular evolutionary stochastic models. First, fractionated spacecraft nomenclature and architecture are clarified, and assessment criteria are analyzed. The mean and standard deviation of risk adjusted lifecycle cost and net present value （NPV） are defined as assessment metrics. Second, fractionated spacecraft sizing models are briefly described, followed by detailed discussion on risk adjusted lifecycle cost and NPV models. Third, uncertainty sources over fractionated spacecraft life- cycle are analyzed and modeled with probability theory. Then the chronological lifecycle simulation process is expounded, and simulation modules are developed with object oriented methodology to build up the assessment tool. The preceding uncertainty models are integrated in these simulation modules, hence the random object status can be simulated and evolve with lifecycle timeline. A case study to investigate the fractionated spacecraft for a hypothetical earth observation mission is carried out with the proposed assessment tool, and the results show that fractionation degree and launch manifest have great influence on cost and NPV, and generally fractionated spacecraft is more advanced than its monolithic counterpart under uncertainty effect. Finally, some conclusions are given and future research topics are highlighted.
基金funded by China Scholarship Council (CSC)and National Science and Technology Major Project,China(No. 2017-V-0015-0067)。
文摘To solve the rapid transient control problem of Flight Environment Simulation System(FESS) of Altitude Ground Test Facilities(AGTF) with large heat transfer uncertainty and disturbance, a new adaptive control structure of modified robust optimal adaptive control is presented.The mathematic modeling of FESS is given and the influence of heat transfer is analyzed through energy view. To consider the influence of heat transfer in controller design, we introduce a matched uncertainty that represents heat transfer influence in the linearized system of FESS. Based on this linear system, we deduce the design of modified robust optimal adaptive control law in a general way. Meanwhile, the robust stability of the modified robust optimal adaptive control law is proved through using Lyapunov stability theory. Then, a typical aero-engine test condition with Mach Dash and Zoom-Climb is used to verify the effectiveness of the devised adaptive controller. The simulation results show that the designed controller has servo tracking and disturbance rejection performance under heat transfer uncertainty and disturbance;the relative steady-state and dynamic errors of pressure and temperature are both smaller than 1% and 0.2% respectively. Furthermore,the influence of the modification parameter c is analyzed through simulation. Finally, comparing with the standard ideal model reference adaptive controller, the modified robust optimal adaptive controller obviously provides better control performance than the ideal model reference adaptive controller does.
基金supported by Research Foundation of Education Bureau of Shannxi Province, PRC(No.2010JK400)
文摘The robust stability and robust stabilization problems for discrete singular systems with interval time-varying delay and linear fractional uncertainty are discussed. A new delay-dependent criterion is established for the nominal discrete singular delay systems to be regular, causal and stable by employing the linear matrix inequality （LMI） approach. It is shown that the newly proposed criterion can provide less conservative results than some existing ones. Then, with this criterion, the problems of robust stability and robust stabilization for uncertain discrete singular delay systems are solved, and the delay-dependent LMI conditions are obtained. Finally, numerical examples are given to illustrate the effectiveness of the proposed approach.
基金jointly supported by the National Key Research and Development Program of China (Grant. No. 2017YFC1501601)the National Natural Science Foundation of China (Grant. No. 41475100)+1 种基金the National Science and Technology Support Program (Grant. No. 2012BAC22B03)the Youth Innovation Promotion Association of the Chinese Academy of Sciences
文摘This paper investigates the possible sources of errors associated with tropical cyclone(TC) tracks forecasted using the Global/Regional Assimilation and Prediction System(GRAPES). In Part I, it is shown that the model error of GRAPES may be the main cause of poor forecasts of landfalling TCs. Thus, a further examination of the model error is the focus of Part II.Considering model error as a type of forcing, the model error can be represented by the combination of good forecasts and bad forecasts. Results show that there are systematic model errors. The model error of the geopotential height component has periodic features, with a period of 24 h and a global pattern of wavenumber 2 from west to east located between 60?S and 60?N. This periodic model error presents similar features as the atmospheric semidiurnal tide, which reflect signals from tropical diabatic heating, indicating that the parameter errors related to the tropical diabatic heating may be the source of the periodic model error. The above model errors are subtracted from the forecast equation and a series of new forecasts are made. The average forecasting capability using the rectified model is improved compared to simply improving the initial conditions of the original GRAPES model. This confirms the strong impact of the periodic model error on landfalling TC track forecasts. Besides, if the model error used to rectify the model is obtained from an examination of additional TCs, the forecasting capabilities of the corresponding rectified model will be improved.
基金Project(60634020) supported by the National Natural Science Foundation of China
文摘Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employed to identify the primary uncertainty and the mathematic model of the system was turned into an equivalent linear model with terms of secondary uncertainty.At the same time,gain adaptive sliding mode variable structure control(GASMVSC) was employed to synthesize the control effort.The results show that the unrealization problem caused by some system's immeasurable state variables in traditional fuzzy neural networks(TFNN) taking all state variables as its inputs is overcome.On the other hand,the identification by the ADRFNNs online with high accuracy and the adaptive function of the correction term's gain in the GASMVSC make the system possess strong robustness and improved steady accuracy,and the chattering phenomenon of the control effort is also suppressed effectively.
