As the core of spatial planning in China,delineation of the production-living-ecological space(PLES)refers to dividing the overall land use into three functional spaces.Spatial units are optimally configured as the mo...As the core of spatial planning in China,delineation of the production-living-ecological space(PLES)refers to dividing the overall land use into three functional spaces.Spatial units are optimally configured as the most suitable functional type,while beset by various uncertainties.Weight uncertainties,being affected by subjective preferences,are highly arbitrary and seriously affect PLES.Taking Xuzhou as the study area,this paper studies the perturbation mechanism and response measure of weight uncertainties on PLES.First,weight samples are obtained through quasi-random sampling to serve as sources of uncertainties for input into the optimized delineation of PLES.Next,the Monte Carlo simulation is applied to simulate the spatial probability distribution of PLES.The global sensitivity analysis method is then adopted to identify the main sources that cause uncertainties in the delineation of PLES.Subsequently,the flexible space(FS)of PLES at a certain level of significance is formulated by comparing the distribution probabilities of spatial units for different functional spaces,acting as a countermeasure for the perturbation.The results show that weight uncertainties bring disturbances to the PLES by affecting the multi-criteria evaluation(MCE)of PLES delineation.The PLES is affected by the weight uncertainties of the factors alone or through interactions with other weights.FS is the spatial response measure of PLES when uncertainties occurred at a certain level of significance.The study introduces the perspective of uncertainty for PLES,which contributes toward improving the scientificity and reliability of PLES.展开更多
Seismic fragility analysis(SFA)is known as an effective probabilistic-based approach used to evaluate seismic fragility.There are various sources of uncertainties associated with this approach.A nuclear power plant(NP...Seismic fragility analysis(SFA)is known as an effective probabilistic-based approach used to evaluate seismic fragility.There are various sources of uncertainties associated with this approach.A nuclear power plant(NPP)system is an extremely important infrastructure and contains many structural uncertainties due to construction issues or structural deterioration during service.Simulation of structural uncertainties effects is a costly and time-consuming endeavor.A novel approach to SFA for the NPP considering structural uncertainties based on the damage state is proposed and examined.The results suggest that considering the structural uncertainties is essential in assessing the fragility of the NPP structure,and the impact of structural uncertainties tends to increase with the state of damage.Subsequently,machine learning(ML)is found to be superior in high-precision damage state identification of the NPP for reducing the time of nonlinear time-history analysis(NLTHA)and could be applied in the damage state-based SFA.Also,the impact of various sources of uncertainties is investigated through sensitivity analysis.The Sobol and Shapley additive explanations(SHAP)method can be complementary to each other and able to solve the problem of quantifying seismic and structural uncertainties simultaneously and the interaction effect of each parameter.展开更多
The evolution of China-ASEAN relations ranks among the most significant geopolitical and economic dynamics of the 21st Century.Comprising 10 Southeast Asian nations,ASEAN has held the position of China’s largest trad...The evolution of China-ASEAN relations ranks among the most significant geopolitical and economic dynamics of the 21st Century.Comprising 10 Southeast Asian nations,ASEAN has held the position of China’s largest trading partner since 2020.This partnership is underpinned by sustained economic growth,political stability,security cooperation,and vibrant socio-cultural exchanges.Over the past two decades,the China-ASEAN relationship has emerged as a main axis in Asia’s geopolitical and economic landscape.By 2025,this partnership has entered a more intricate and strategic phase marked by deeper economic collaboration,expanded multilateral diplomacy,and mounting challenges stemming from global developments such as tari"wars and South China Sea tensions.展开更多
The increasingly stringent performance requirement in integrated circuit manufacturing, characterized by smaller feature sizes and higher productivity, necessitates the wafer stage executing a extreme motion with the ...The increasingly stringent performance requirement in integrated circuit manufacturing, characterized by smaller feature sizes and higher productivity, necessitates the wafer stage executing a extreme motion with the accuracy in terms of nanometers. This demanding requirement witnesses a widespread application of iterative learning control(ILC), given the repetitive nature of wafer scanning. ILC enables substantial performance improvement by using past measurement data in combination with the system model knowledge. However, challenges arise in cases where the data is contaminated by the stochastic noise, or when the system model exhibits significant uncertainties, constraining the achievable performance. In response to this issue, an extended state observer(ESO) based adaptive ILC approach is proposed in the frequency domain.Despite being model-based, it utilizes only a rough system model and then compensates for the resulting model uncertainties using an ESO, thereby achieving high robustness against uncertainties with minimal modeling effort. Additionally, an adaptive learning law is developed to mitigate the limited performance in the presence of stochastic noise, yielding high convergence accuracy yet without compromising convergence speed. Simulation and experimental comparisons with existing model-based and data-driven inversion-based ILC validate the effectiveness as well as the superiority of the proposed method.展开更多
This paper designs distributed Nash equilibrium seeking strategies for heterogeneous dynamic cyber-physical systems.In particular, we are concerned with parametric uncertainties in the control channel of the players. ...This paper designs distributed Nash equilibrium seeking strategies for heterogeneous dynamic cyber-physical systems.In particular, we are concerned with parametric uncertainties in the control channel of the players. Moreover, the weights on communication links can be compromised by time-varying uncertainties, which can result from possibly malicious attacks,faults and disturbances. To deal with the unavailability of measurement of optimization errors, an output observer is constructed,based on which adaptive laws are designed to compensate for physical uncertainties. With adaptive laws, a new distributed Nash equilibrium seeking strategy is designed by further integrating consensus protocols and gradient search algorithms.Moreover, to further accommodate compromised communication weights resulting from cyber-uncertainties, the coupling strengths of the consensus module are designed to be adaptive. As a byproduct, the coupling strengths are independent of any global information. With theoretical investigations, it is proven that the proposed strategies are resilient to these uncertainties and players' actions are convergent to the Nash equilibrium. Simulation examples are given to numerically validate the effectiveness of the proposed strategies.展开更多
Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan ...Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan is one of the crucial issues in shipbuilding.In this paper,production scheduling and material ordering with endogenous uncertainty of the outfitting process are investigated.The uncertain factors in outfitting equipment production are usually decision-related,which leads to difficulties in addressing uncertainties in the outfitting production workshops before production is conducted according to plan.This uncertainty is regarded as endogenous uncertainty and can be treated as non-anticipativity constraints in the model.To address this problem,a stochastic two-stage programming model with endogenous uncertainty is established to optimize the outfitting job scheduling and raw material ordering process.A practical case of the shipyard of China Merchants Heavy Industry Co.,Ltd.is used to evaluate the performance of the proposed method.Satisfactory results are achieved at the lowest expected total cost as the complete kit rate of outfitting equipment is improved and emergency replenishment is reduced.展开更多
Robustness against measurement uncertainties is crucial for gas turbine engine diagnosis.While current research focuses mainly on measurement noise,measurement bias remains challenging.This study proposes a novel perf...Robustness against measurement uncertainties is crucial for gas turbine engine diagnosis.While current research focuses mainly on measurement noise,measurement bias remains challenging.This study proposes a novel performance-based fault detection and identification(FDI)strategy for twin-shaft turbofan gas turbine engines and addresses these uncertainties through a first-order Takagi-Sugeno-Kang fuzzy inference system.To handle ambient condition changes,we use parameter correction to preprocess the raw measurement data,which reduces the FDI’s system complexity.Additionally,the power-level angle is set as a scheduling parameter to reduce the number of rules in the TSK-based FDI system.The data for designing,training,and testing the proposed FDI strategy are generated using a component-level turbofan engine model.The antecedent and consequent parameters of the TSK-based FDI system are optimized using the particle swarm optimization algorithm and ridge regression.A robust structure combining a specialized fuzzy inference system with the TSK-based FDI system is proposed to handle measurement biases.The performance of the first-order TSK-based FDI system and robust FDI structure are evaluated through comprehensive simulation studies.Comparative studies confirm the superior accuracy of the first-order TSK-based FDI system in fault detection,isolation,and identification.The robust structure demonstrates a 2%-8%improvement in the success rate index under relatively large measurement bias conditions,thereby indicating excellent robustness.Accuracy against significant bias values and computation time are also evaluated,suggesting that the proposed robust structure has desirable online performance.This study proposes a novel FDI strategy that effectively addresses measurement uncertainties.展开更多
To take into account the influence of uncetainties on the dynamic response of the vibro-acousitc structure, a hybrid modeling technique combining the finite element method（FE）and the statistic energy analysis（SEA）...To take into account the influence of uncetainties on the dynamic response of the vibro-acousitc structure, a hybrid modeling technique combining the finite element method（FE）and the statistic energy analysis（SEA） is proposed to analyze vibro-acoustics responses with uncertainties at middle frequencies. The mid-frequency dynamic response of the framework-plate structure with uncertainties is studied based on the hybrid FE-SEA method and the Monte Carlo（MC）simulation is performed so as to provide a benchmark comparison with the hybrid method. The energy response of the framework-plate structure matches well with the MC simulation results, which validates the effectiveness of the hybrid FE-SEA method considering both the complexity of the vibro-acoustic structure and the uncertainties in mid-frequency vibro-acousitc analysis. Based on the hybrid method, a vibroacoustic model of a construction machinery cab with random properties is established, and the excitations of the model are measured by experiments. The responses of the sound pressure level of the cab and the vibration power spectrum density of the front windscreen are calculated and compared with those of the experiment. At middle frequencies, the results have a good consistency with the tests and the prediction error is less than 3. 5dB.展开更多
The continuously increasing renewable energy sources(RES)and demand response(DR)are becoming crucial sources of system flexibility.Consequently,decision-dependent uncertainties(DDUs),inter-changeably referred to as en...The continuously increasing renewable energy sources(RES)and demand response(DR)are becoming crucial sources of system flexibility.Consequently,decision-dependent uncertainties(DDUs),inter-changeably referred to as endogenous uncertainties,impose new characteristics on power system dis-patch.The DDUs faced by system operators originate from uncertain dispatchable resources such as RES units or DR,while reserve providers encounter DDUs from the uncertain reserve deployment.Thus,a systematic framework was established in this study to address robust dispatch problems with DDUs.The main contributions are drawn as follows.①The robust characterization of DDUs was unfolded with a dependency decomposition structure.②A generic DDU coping mechanism was manifested as the bilateral matching between uncertainty and flexibility.③The influence of DDU incorporation on the convexity/non-convexity of robust dispatch problems was analyzed.④Generic solution algorithms adaptive for DDUs were proposed.Under this framework,the inherent distinctions and correlations between DDUs and decision-independent uncertainties(DIUs)were revealed,laying a fundamental theoretical foundation for the economic and reliable operation of RES-dominated power systems.Illustrative applications in the source and demand sides are provided to show the significance of considering DDUs and demonstrate the proposed theoretical results.展开更多
Accurate estimation of rockfall trajectories is essential for mitigation of rockfall hazards.Nowadays,Doppler radar technologies can measure rockfall trajectories with centimeter resolution.Calibrating a numerical mod...Accurate estimation of rockfall trajectories is essential for mitigation of rockfall hazards.Nowadays,Doppler radar technologies can measure rockfall trajectories with centimeter resolution.Calibrating a numerical model to fit these measured trajectories,i.e.back analysis,often involves manual trial-anderror processes and subjective goodness-of-fit criteria.Here,we propose a framework that uses the chi-square statistic to quantify the misfit between modeled and measured rockfall trajectories.The framework can also quantify the uncertainty bounds on the best-fit model parameters.The approach is validated using field data from an Australian copper mine under two scenarios.(1)We perform an unconstrained back-analysis where the initial position and velocity of the rock,in addition to the coefficients of restitution(COR),are free variables.This scenario yields a normal COR Rn?0.866±0.109 and tangential COR R_(t)=0.29±0.151 with 68%confidence.(2)We perform a constrained back-analysis using predetermined initial position and velocity of the rock,which further constrains Rn to 0.8±0.014 and Rt to 0.39±0.065.Both scenarios show a higher uncertainty in Rt than in Rn.We also demonstrate the adaptability of the back-analysis framework to two-dimensional(2D)rockfall modeling using the same data.To the best of our knowledge,this is the first quantitative goodness-of-fit metric for trajectorybased rockfall back analysis that supports the estimation of inherent uncertainty.The simplicity of the metric lends itself to robust model optimization of rockfall back-analysis and can be adapted to other model assumptions(e.g.rigid-body mechanics)and metrics(e.g.velocity or energy).展开更多
The Reliability-Based Design Optimization(RBDO)of complex engineering structures considering uncertainties has problems of being high-dimensional,highly nonlinear,and timeconsuming,which requires a significant amount ...The Reliability-Based Design Optimization(RBDO)of complex engineering structures considering uncertainties has problems of being high-dimensional,highly nonlinear,and timeconsuming,which requires a significant amount of sampling simulation computation.In this paper,a basis-adaptive Polynomial Chaos(PC)-Kriging surrogate model is proposed,in order to relieve the computational burden and enhance the predictive accuracy of a metamodel.The active learning basis-adaptive PC-Kriging model is combined with a quantile-based RBDO framework.Finally,five engineering cases have been implemented,including a benchmark RBDO problem,three high-dimensional explicit problems,and a high-dimensional implicit problem.Compared with Support Vector Regression(SVR),Kriging,and polynomial chaos expansion models,results show that the proposed basis-adaptive PC-Kriging model is more accurate and efficient for RBDO problems of complex engineering structures.展开更多
Thermal Protection System(TPS)with thick tiles,low thermal conductivity,and a short re-entry stage stands as a critical element within reusable aircraft,whose reliability is related to the function and changes with th...Thermal Protection System(TPS)with thick tiles,low thermal conductivity,and a short re-entry stage stands as a critical element within reusable aircraft,whose reliability is related to the function and changes with their physical properties,external conditions,and degradation.Meanwhile,due to the limitation of testing resources,epistemic uncertainties stemming from the small samples are present in TPS reliability modeling.However,current TPS reliability modeling methods face challenges in characterizing the relationships among reliability and physical properties,external conditions,degradation,and epistemic uncertainties.Therefore,under the framework of belief reliability theory,a TPS reliability model is constructed,which takes into account the physical principle,external conditions,performance degradation,and epistemic uncertainties.A reliability simulation algorithm is proposed to calculate TPS reliability.Through a case study and comparison analysis,the proposed method is validated as more effective than the existing method.Additionally,reliability sensitivity analysis is conducted to identify the sensitive factors of reliability under the condition of small samples,through which suggestions are provided for TPS functional design and improvement.展开更多
This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems posses...This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.展开更多
From the perspective of state-channel interaction,standard quantum teleportation can be viewed as a communication process characterized by both input and output,functioning as a quantum depolarizing channel.To achieve...From the perspective of state-channel interaction,standard quantum teleportation can be viewed as a communication process characterized by both input and output,functioning as a quantum depolarizing channel.To achieve a precise quantification of the quantumness introduced by this channel,we examine its uncertainties,which encompass both statedependent and state-independent uncertainties.Specifically,for qudit systems,we provide general formulas for these uncertainties.We analyze the uncertainties associated with standard quantum teleportation when induced by isotropic states,Werner states,and X-states,and we elucidate the correlation between these uncertainties and the parameters of the specific mixed states.Our findings demonstrate the validity of quantifying these uncertainties.展开更多
This study introduces a real-time data-driven battery management scheme designed to address uncertainties in load and generation forecasts,which are integral to an optimal energy storage control system.By expanding on...This study introduces a real-time data-driven battery management scheme designed to address uncertainties in load and generation forecasts,which are integral to an optimal energy storage control system.By expanding on an existing algorithm,this study resolves issues discovered during implementation and addresses previously overlooked concerns,resulting in significant enhancements in both performance and reliability.The refined real-time control scheme is integrated with a day-ahead optimization engine and forecast model,which is utilized for illustrative simulations to highlight its potential efficacy on a real site.Furthermore,a comprehensive comparison with the original formulation was conducted to cover all possible scenarios.This analysis validated the operational effectiveness of the scheme and provided a detailed evaluation of the improvements and expected behavior of the control system.Incorrect or improper adjustments to mitigate forecast uncertainties can result in suboptimal energy management,significant financial losses and penalties,and potential contract violations.The revised algorithm optimizes the operation of the battery system in real time and safeguards its state of health by limiting the charging/discharging cycles and enforcing adherence to contractual agreements.These advancements yield a reliable and efficient real-time correction algorithm for optimal site management,designed as an independent white box that can be integrated with any day-ahead optimization control system.展开更多
The determination of the dynamic load is one of the indispensable technologies for structure design and health monitoring for aerospace vehicles.However,it is a significant challenge to measure the external excitation...The determination of the dynamic load is one of the indispensable technologies for structure design and health monitoring for aerospace vehicles.However,it is a significant challenge to measure the external excitation directly.By contrast,the technique of dynamic load identification based on the dynamic model and the response information is a feasible access to obtain the dynamic load indirectly.Furthermore,there are multi-source uncertainties which cannot be neglected for complex systems in the load identification process,especially for aerospace vehicles.In this paper,recent developments in the dynamic load identification field for aerospace vehicles considering multi-source uncertainties are reviewed,including the deterministic dynamic load identification and uncertain dynamic load identification.The inversion methods with different principles of concentrated and distributed loads,and the quantification and propagation analysis for multi-source uncertainties are discussed.Eventually,several possibilities remaining to be explored are illustrated in brief.展开更多
Aim The solvability condition for robust stabilization problem associated with a plant family P(s,δ) having parameter uncertainty δ was considered. Methods Using Youla parameterization of the stabilizers this pro...Aim The solvability condition for robust stabilization problem associated with a plant family P(s,δ) having parameter uncertainty δ was considered. Methods Using Youla parameterization of the stabilizers this problem was transformed into a strong stabilization problem associated with a related plant family G (s, δ). Results A necessary solvability condition was established in terms of the parity interlacing property of each element in G(s,δ). Another apparently necessary solvability condition is that every element in P(s,δ) must be stabilizable. Conclusion The two conditions will be compared with each other and it will be shown that every element in G(s,δ) possesses parity interlacing property if P(s,δ) is stabilizable.展开更多
The dynamic influence of joints in aero-engine rotor systems is investigated in this paper.Firstly,the tangential stiffness and loss factor are obtained from an isolated lap joint setup with dynamic excitation experim...The dynamic influence of joints in aero-engine rotor systems is investigated in this paper.Firstly,the tangential stiffness and loss factor are obtained from an isolated lap joint setup with dynamic excitation experiments.Also,the influence of the normal contact pressure and the excitation level are examined,which revel the uncertainty in joints.Then,the updated Thin Layer Elements(TLEs)method with fitted parameters based on the experiments is established to simulate the dynamic properties of joints on the interface.The response of the rotor subjected to unbalance excitation is calculated,and the results illustrate the effectiveness of the proposed method.Meanwhile,using the Chebyshev inclusion function and a direct iteration algorithm,a nonlinear interval analysis method is established to consider the uncertainty of parameters in joints.The accuracy is proved by comparison with results obtained using the Monte-Carlo method.Combined with the updated TLEs,the nonlinear Chebyshev method is successfully applied on a finite model of a rotor.The study shows that substantial attention should be paid to the dynamical design for the joint in rotor systems,the dynamic properties of joints under complex loading and the corresponding interval analysis method need to be intensively studied.展开更多
In this paper,the satellite attitude control system subject to parametric perturbations,external disturbances,time-varying input delays,actuator faults and saturation is studied.In order to make the controller archite...In this paper,the satellite attitude control system subject to parametric perturbations,external disturbances,time-varying input delays,actuator faults and saturation is studied.In order to make the controller architecture simple and practical,the closed-loop system is transformed into a disturbance-free nominal system and an equivalent disturbance firstly.The equivalent disturbance represents all above uncertainties and actuator failures of the original system.Then a robust controller is proposed in a simple composition consisting of a nominal controller and a robust compensator.The nominal controller is designed for the transformed nominal system.The robust compensator is developed from a second-order filter to restrict the influence of the equivalent disturbance.Stability analysis indicates that both attitude tracking errors and compensator states can converge into the given neighborhood of the origin in finite time.To verify the effectiveness of the proposed control law,numerical simulations are carried out in different cases.Presented results demonstrate that the high-precision attitude tracking control can be achieved by the proposed fault-tolerant control law.Furthermore,multiple system performances including the control accuracy and energy consumption index are fully discussed under a series of compensator parameters.展开更多
Drilling and blasting are the two most significant operations in open pit mines that play a crucial role in downstream stages. While previous research has focused on optimizing these operations as two separate parts o...Drilling and blasting are the two most significant operations in open pit mines that play a crucial role in downstream stages. While previous research has focused on optimizing these operations as two separate parts or merely in a specific parameter, this paper proposes a system dynamic model(SDM) for drilling and blasting operations as an interactive system. In addition, some technical and economic uncertainties such as rock density, uniaxial compressive strength, bit life and operating costs are considered in this system to evaluate the different optimization results. For this purpose, Vensim simulation software is utilized as a powerful dynamic tool for both modelling and optimizing under deterministic and uncertain conditions. It is concluded that an integrated optimization as opposed to the deterministic approach can be efficiently achieved. This however is dependent on the parameters that are considered as uncertainties.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.42171248,42371273)。
文摘As the core of spatial planning in China,delineation of the production-living-ecological space(PLES)refers to dividing the overall land use into three functional spaces.Spatial units are optimally configured as the most suitable functional type,while beset by various uncertainties.Weight uncertainties,being affected by subjective preferences,are highly arbitrary and seriously affect PLES.Taking Xuzhou as the study area,this paper studies the perturbation mechanism and response measure of weight uncertainties on PLES.First,weight samples are obtained through quasi-random sampling to serve as sources of uncertainties for input into the optimized delineation of PLES.Next,the Monte Carlo simulation is applied to simulate the spatial probability distribution of PLES.The global sensitivity analysis method is then adopted to identify the main sources that cause uncertainties in the delineation of PLES.Subsequently,the flexible space(FS)of PLES at a certain level of significance is formulated by comparing the distribution probabilities of spatial units for different functional spaces,acting as a countermeasure for the perturbation.The results show that weight uncertainties bring disturbances to the PLES by affecting the multi-criteria evaluation(MCE)of PLES delineation.The PLES is affected by the weight uncertainties of the factors alone or through interactions with other weights.FS is the spatial response measure of PLES when uncertainties occurred at a certain level of significance.The study introduces the perspective of uncertainty for PLES,which contributes toward improving the scientificity and reliability of PLES.
基金National Natural Science Foundation of China under Grant Nos.52208191 and 51908397Shanxi Province Science Foundation for Youths under Grant No.201901D211025China Postdoctoral Science Foundation under Grant No.2020M670695。
文摘Seismic fragility analysis(SFA)is known as an effective probabilistic-based approach used to evaluate seismic fragility.There are various sources of uncertainties associated with this approach.A nuclear power plant(NPP)system is an extremely important infrastructure and contains many structural uncertainties due to construction issues or structural deterioration during service.Simulation of structural uncertainties effects is a costly and time-consuming endeavor.A novel approach to SFA for the NPP considering structural uncertainties based on the damage state is proposed and examined.The results suggest that considering the structural uncertainties is essential in assessing the fragility of the NPP structure,and the impact of structural uncertainties tends to increase with the state of damage.Subsequently,machine learning(ML)is found to be superior in high-precision damage state identification of the NPP for reducing the time of nonlinear time-history analysis(NLTHA)and could be applied in the damage state-based SFA.Also,the impact of various sources of uncertainties is investigated through sensitivity analysis.The Sobol and Shapley additive explanations(SHAP)method can be complementary to each other and able to solve the problem of quantifying seismic and structural uncertainties simultaneously and the interaction effect of each parameter.
文摘The evolution of China-ASEAN relations ranks among the most significant geopolitical and economic dynamics of the 21st Century.Comprising 10 Southeast Asian nations,ASEAN has held the position of China’s largest trading partner since 2020.This partnership is underpinned by sustained economic growth,political stability,security cooperation,and vibrant socio-cultural exchanges.Over the past two decades,the China-ASEAN relationship has emerged as a main axis in Asia’s geopolitical and economic landscape.By 2025,this partnership has entered a more intricate and strategic phase marked by deeper economic collaboration,expanded multilateral diplomacy,and mounting challenges stemming from global developments such as tari"wars and South China Sea tensions.
基金supported by National Natural Science Foundation of China(52375530,52075132)Natural Science Foundation of Heilongjiang Province(YQ2022E025)+4 种基金State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment(Guangdong University of Technology)(JMDZ202312)Fundamental Research Funds for the Central Universities(HIT.OCEF.2024034)China Postdoctoral Science Foundation(2019M651278,2020T130155)Heilongjiang Province Postdoctoral Science Foundation(LBH-Z19066)Space Drive and Manipulation Mechanism Laboratory of BICE and National Key Laboratory of Space Intelligent Control,No BICE-SDMM-2024-01
文摘The increasingly stringent performance requirement in integrated circuit manufacturing, characterized by smaller feature sizes and higher productivity, necessitates the wafer stage executing a extreme motion with the accuracy in terms of nanometers. This demanding requirement witnesses a widespread application of iterative learning control(ILC), given the repetitive nature of wafer scanning. ILC enables substantial performance improvement by using past measurement data in combination with the system model knowledge. However, challenges arise in cases where the data is contaminated by the stochastic noise, or when the system model exhibits significant uncertainties, constraining the achievable performance. In response to this issue, an extended state observer(ESO) based adaptive ILC approach is proposed in the frequency domain.Despite being model-based, it utilizes only a rough system model and then compensates for the resulting model uncertainties using an ESO, thereby achieving high robustness against uncertainties with minimal modeling effort. Additionally, an adaptive learning law is developed to mitigate the limited performance in the presence of stochastic noise, yielding high convergence accuracy yet without compromising convergence speed. Simulation and experimental comparisons with existing model-based and data-driven inversion-based ILC validate the effectiveness as well as the superiority of the proposed method.
基金supported by the National Key R&D Program of China(2022ZD0119604)the National Natural Science Foundation of China(NSFC)(62173181,62222308,62221004)the Natural Science Foundation of Jiangsu Province(BK20220139)
文摘This paper designs distributed Nash equilibrium seeking strategies for heterogeneous dynamic cyber-physical systems.In particular, we are concerned with parametric uncertainties in the control channel of the players. Moreover, the weights on communication links can be compromised by time-varying uncertainties, which can result from possibly malicious attacks,faults and disturbances. To deal with the unavailability of measurement of optimization errors, an output observer is constructed,based on which adaptive laws are designed to compensate for physical uncertainties. With adaptive laws, a new distributed Nash equilibrium seeking strategy is designed by further integrating consensus protocols and gradient search algorithms.Moreover, to further accommodate compromised communication weights resulting from cyber-uncertainties, the coupling strengths of the consensus module are designed to be adaptive. As a byproduct, the coupling strengths are independent of any global information. With theoretical investigations, it is proven that the proposed strategies are resilient to these uncertainties and players' actions are convergent to the Nash equilibrium. Simulation examples are given to numerically validate the effectiveness of the proposed strategies.
基金supported in part by the High-tech ship scientific research project of the Ministry of Industry and Information Technology of the People’s Republic of China,and the National Nature Science Foundation of China(Grant No.71671113)the Science and Technology Department of Shaanxi Province(No.2020GY-219)the Ministry of Education Collaborative Project of Production,Learning and Research(No.201901024016).
文摘Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan is one of the crucial issues in shipbuilding.In this paper,production scheduling and material ordering with endogenous uncertainty of the outfitting process are investigated.The uncertain factors in outfitting equipment production are usually decision-related,which leads to difficulties in addressing uncertainties in the outfitting production workshops before production is conducted according to plan.This uncertainty is regarded as endogenous uncertainty and can be treated as non-anticipativity constraints in the model.To address this problem,a stochastic two-stage programming model with endogenous uncertainty is established to optimize the outfitting job scheduling and raw material ordering process.A practical case of the shipyard of China Merchants Heavy Industry Co.,Ltd.is used to evaluate the performance of the proposed method.Satisfactory results are achieved at the lowest expected total cost as the complete kit rate of outfitting equipment is improved and emergency replenishment is reduced.
文摘Robustness against measurement uncertainties is crucial for gas turbine engine diagnosis.While current research focuses mainly on measurement noise,measurement bias remains challenging.This study proposes a novel performance-based fault detection and identification(FDI)strategy for twin-shaft turbofan gas turbine engines and addresses these uncertainties through a first-order Takagi-Sugeno-Kang fuzzy inference system.To handle ambient condition changes,we use parameter correction to preprocess the raw measurement data,which reduces the FDI’s system complexity.Additionally,the power-level angle is set as a scheduling parameter to reduce the number of rules in the TSK-based FDI system.The data for designing,training,and testing the proposed FDI strategy are generated using a component-level turbofan engine model.The antecedent and consequent parameters of the TSK-based FDI system are optimized using the particle swarm optimization algorithm and ridge regression.A robust structure combining a specialized fuzzy inference system with the TSK-based FDI system is proposed to handle measurement biases.The performance of the first-order TSK-based FDI system and robust FDI structure are evaluated through comprehensive simulation studies.Comparative studies confirm the superior accuracy of the first-order TSK-based FDI system in fault detection,isolation,and identification.The robust structure demonstrates a 2%-8%improvement in the success rate index under relatively large measurement bias conditions,thereby indicating excellent robustness.Accuracy against significant bias values and computation time are also evaluated,suggesting that the proposed robust structure has desirable online performance.This study proposes a novel FDI strategy that effectively addresses measurement uncertainties.
基金Science and Technology Support Planning of Jiangsu Province(No.BE2014133)the Open Foundation of Key Laboratory of Underw ater Acoustic Signal Processing(No.UASP1301)the Prospective Joint Research Project of Jiangsu province(No.BY2014127-01)
文摘To take into account the influence of uncetainties on the dynamic response of the vibro-acousitc structure, a hybrid modeling technique combining the finite element method（FE）and the statistic energy analysis（SEA） is proposed to analyze vibro-acoustics responses with uncertainties at middle frequencies. The mid-frequency dynamic response of the framework-plate structure with uncertainties is studied based on the hybrid FE-SEA method and the Monte Carlo（MC）simulation is performed so as to provide a benchmark comparison with the hybrid method. The energy response of the framework-plate structure matches well with the MC simulation results, which validates the effectiveness of the hybrid FE-SEA method considering both the complexity of the vibro-acoustic structure and the uncertainties in mid-frequency vibro-acousitc analysis. Based on the hybrid method, a vibroacoustic model of a construction machinery cab with random properties is established, and the excitations of the model are measured by experiments. The responses of the sound pressure level of the cab and the vibration power spectrum density of the front windscreen are calculated and compared with those of the experiment. At middle frequencies, the results have a good consistency with the tests and the prediction error is less than 3. 5dB.
基金supported by the Joint Research Fund in Smart Grid(U1966601)under cooperative agreement between the National Natural Science Foundation of China(NSFC)and State Grid Corporation of China.
文摘The continuously increasing renewable energy sources(RES)and demand response(DR)are becoming crucial sources of system flexibility.Consequently,decision-dependent uncertainties(DDUs),inter-changeably referred to as endogenous uncertainties,impose new characteristics on power system dis-patch.The DDUs faced by system operators originate from uncertain dispatchable resources such as RES units or DR,while reserve providers encounter DDUs from the uncertain reserve deployment.Thus,a systematic framework was established in this study to address robust dispatch problems with DDUs.The main contributions are drawn as follows.①The robust characterization of DDUs was unfolded with a dependency decomposition structure.②A generic DDU coping mechanism was manifested as the bilateral matching between uncertainty and flexibility.③The influence of DDU incorporation on the convexity/non-convexity of robust dispatch problems was analyzed.④Generic solution algorithms adaptive for DDUs were proposed.Under this framework,the inherent distinctions and correlations between DDUs and decision-independent uncertainties(DIUs)were revealed,laying a fundamental theoretical foundation for the economic and reliable operation of RES-dominated power systems.Illustrative applications in the source and demand sides are provided to show the significance of considering DDUs and demonstrate the proposed theoretical results.
基金funding from NSERC Alliance Grant ALLRP 576858e22 in partnership with Rocscience Inc.
文摘Accurate estimation of rockfall trajectories is essential for mitigation of rockfall hazards.Nowadays,Doppler radar technologies can measure rockfall trajectories with centimeter resolution.Calibrating a numerical model to fit these measured trajectories,i.e.back analysis,often involves manual trial-anderror processes and subjective goodness-of-fit criteria.Here,we propose a framework that uses the chi-square statistic to quantify the misfit between modeled and measured rockfall trajectories.The framework can also quantify the uncertainty bounds on the best-fit model parameters.The approach is validated using field data from an Australian copper mine under two scenarios.(1)We perform an unconstrained back-analysis where the initial position and velocity of the rock,in addition to the coefficients of restitution(COR),are free variables.This scenario yields a normal COR Rn?0.866±0.109 and tangential COR R_(t)=0.29±0.151 with 68%confidence.(2)We perform a constrained back-analysis using predetermined initial position and velocity of the rock,which further constrains Rn to 0.8±0.014 and Rt to 0.39±0.065.Both scenarios show a higher uncertainty in Rt than in Rn.We also demonstrate the adaptability of the back-analysis framework to two-dimensional(2D)rockfall modeling using the same data.To the best of our knowledge,this is the first quantitative goodness-of-fit metric for trajectorybased rockfall back analysis that supports the estimation of inherent uncertainty.The simplicity of the metric lends itself to robust model optimization of rockfall back-analysis and can be adapted to other model assumptions(e.g.rigid-body mechanics)and metrics(e.g.velocity or energy).
基金supported by the National Key R&D Program of China(No.2021YFB1715000)the National Natural Science Foundation of China(No.52375073)。
文摘The Reliability-Based Design Optimization(RBDO)of complex engineering structures considering uncertainties has problems of being high-dimensional,highly nonlinear,and timeconsuming,which requires a significant amount of sampling simulation computation.In this paper,a basis-adaptive Polynomial Chaos(PC)-Kriging surrogate model is proposed,in order to relieve the computational burden and enhance the predictive accuracy of a metamodel.The active learning basis-adaptive PC-Kriging model is combined with a quantile-based RBDO framework.Finally,five engineering cases have been implemented,including a benchmark RBDO problem,three high-dimensional explicit problems,and a high-dimensional implicit problem.Compared with Support Vector Regression(SVR),Kriging,and polynomial chaos expansion models,results show that the proposed basis-adaptive PC-Kriging model is more accurate and efficient for RBDO problems of complex engineering structures.
基金supported by the steady supports scientific research of Key Laboratory of Defense Science and Technology,China(No.WDZC20220105)the National Natural Science Foundation of China(Nos.51775020,62073009,U20B2002)the Science Challenge Project,China(No.TZ2018007)。
文摘Thermal Protection System(TPS)with thick tiles,low thermal conductivity,and a short re-entry stage stands as a critical element within reusable aircraft,whose reliability is related to the function and changes with their physical properties,external conditions,and degradation.Meanwhile,due to the limitation of testing resources,epistemic uncertainties stemming from the small samples are present in TPS reliability modeling.However,current TPS reliability modeling methods face challenges in characterizing the relationships among reliability and physical properties,external conditions,degradation,and epistemic uncertainties.Therefore,under the framework of belief reliability theory,a TPS reliability model is constructed,which takes into account the physical principle,external conditions,performance degradation,and epistemic uncertainties.A reliability simulation algorithm is proposed to calculate TPS reliability.Through a case study and comparison analysis,the proposed method is validated as more effective than the existing method.Additionally,reliability sensitivity analysis is conducted to identify the sensitive factors of reliability under the condition of small samples,through which suggestions are provided for TPS functional design and improvement.
基金supported by the fund of Beijing Municipal Commission of Education(KM202210017001 and 22019821001)the Natural Science Foundation of Henan Province(222300420253).
文摘This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.
基金Project supported by the National Natural Science Foundation of China(Grant No.12201300).
文摘From the perspective of state-channel interaction,standard quantum teleportation can be viewed as a communication process characterized by both input and output,functioning as a quantum depolarizing channel.To achieve a precise quantification of the quantumness introduced by this channel,we examine its uncertainties,which encompass both statedependent and state-independent uncertainties.Specifically,for qudit systems,we provide general formulas for these uncertainties.We analyze the uncertainties associated with standard quantum teleportation when induced by isotropic states,Werner states,and X-states,and we elucidate the correlation between these uncertainties and the parameters of the specific mixed states.Our findings demonstrate the validity of quantifying these uncertainties.
基金supported by the Israeli Ministry of Infrastructure,Energy and Water Resources.
文摘This study introduces a real-time data-driven battery management scheme designed to address uncertainties in load and generation forecasts,which are integral to an optimal energy storage control system.By expanding on an existing algorithm,this study resolves issues discovered during implementation and addresses previously overlooked concerns,resulting in significant enhancements in both performance and reliability.The refined real-time control scheme is integrated with a day-ahead optimization engine and forecast model,which is utilized for illustrative simulations to highlight its potential efficacy on a real site.Furthermore,a comprehensive comparison with the original formulation was conducted to cover all possible scenarios.This analysis validated the operational effectiveness of the scheme and provided a detailed evaluation of the improvements and expected behavior of the control system.Incorrect or improper adjustments to mitigate forecast uncertainties can result in suboptimal energy management,significant financial losses and penalties,and potential contract violations.The revised algorithm optimizes the operation of the battery system in real time and safeguards its state of health by limiting the charging/discharging cycles and enforcing adherence to contractual agreements.These advancements yield a reliable and efficient real-time correction algorithm for optimal site management,designed as an independent white box that can be integrated with any day-ahead optimization control system.
基金supported by the National Nature Science Foundation of China(No.12072007)the Ningbo Nature Science Foundation(No.202003N4018)+1 种基金the Aeronautical Science Foundation of China (No. 20182951014)the Defense Industrial Technology Development Program(No.JCKY2019209C004)
文摘The determination of the dynamic load is one of the indispensable technologies for structure design and health monitoring for aerospace vehicles.However,it is a significant challenge to measure the external excitation directly.By contrast,the technique of dynamic load identification based on the dynamic model and the response information is a feasible access to obtain the dynamic load indirectly.Furthermore,there are multi-source uncertainties which cannot be neglected for complex systems in the load identification process,especially for aerospace vehicles.In this paper,recent developments in the dynamic load identification field for aerospace vehicles considering multi-source uncertainties are reviewed,including the deterministic dynamic load identification and uncertain dynamic load identification.The inversion methods with different principles of concentrated and distributed loads,and the quantification and propagation analysis for multi-source uncertainties are discussed.Eventually,several possibilities remaining to be explored are illustrated in brief.
文摘Aim The solvability condition for robust stabilization problem associated with a plant family P(s,δ) having parameter uncertainty δ was considered. Methods Using Youla parameterization of the stabilizers this problem was transformed into a strong stabilization problem associated with a related plant family G (s, δ). Results A necessary solvability condition was established in terms of the parity interlacing property of each element in G(s,δ). Another apparently necessary solvability condition is that every element in P(s,δ) must be stabilizable. Conclusion The two conditions will be compared with each other and it will be shown that every element in G(s,δ) possesses parity interlacing property if P(s,δ) is stabilizable.
基金supported by the National Natural Science Foundation of China(Nos.51575022,11772022 and 51475021).
文摘The dynamic influence of joints in aero-engine rotor systems is investigated in this paper.Firstly,the tangential stiffness and loss factor are obtained from an isolated lap joint setup with dynamic excitation experiments.Also,the influence of the normal contact pressure and the excitation level are examined,which revel the uncertainty in joints.Then,the updated Thin Layer Elements(TLEs)method with fitted parameters based on the experiments is established to simulate the dynamic properties of joints on the interface.The response of the rotor subjected to unbalance excitation is calculated,and the results illustrate the effectiveness of the proposed method.Meanwhile,using the Chebyshev inclusion function and a direct iteration algorithm,a nonlinear interval analysis method is established to consider the uncertainty of parameters in joints.The accuracy is proved by comparison with results obtained using the Monte-Carlo method.Combined with the updated TLEs,the nonlinear Chebyshev method is successfully applied on a finite model of a rotor.The study shows that substantial attention should be paid to the dynamical design for the joint in rotor systems,the dynamic properties of joints under complex loading and the corresponding interval analysis method need to be intensively studied.
基金supported by the APSCO(Asia-Pacific Space Cooperation Organization)Student Small Satellite(SSS)Project(Microsatellite SSS-1,No.APSCO/ET&DM/SSS/IMP_C_001)。
文摘In this paper,the satellite attitude control system subject to parametric perturbations,external disturbances,time-varying input delays,actuator faults and saturation is studied.In order to make the controller architecture simple and practical,the closed-loop system is transformed into a disturbance-free nominal system and an equivalent disturbance firstly.The equivalent disturbance represents all above uncertainties and actuator failures of the original system.Then a robust controller is proposed in a simple composition consisting of a nominal controller and a robust compensator.The nominal controller is designed for the transformed nominal system.The robust compensator is developed from a second-order filter to restrict the influence of the equivalent disturbance.Stability analysis indicates that both attitude tracking errors and compensator states can converge into the given neighborhood of the origin in finite time.To verify the effectiveness of the proposed control law,numerical simulations are carried out in different cases.Presented results demonstrate that the high-precision attitude tracking control can be achieved by the proposed fault-tolerant control law.Furthermore,multiple system performances including the control accuracy and energy consumption index are fully discussed under a series of compensator parameters.
文摘Drilling and blasting are the two most significant operations in open pit mines that play a crucial role in downstream stages. While previous research has focused on optimizing these operations as two separate parts or merely in a specific parameter, this paper proposes a system dynamic model(SDM) for drilling and blasting operations as an interactive system. In addition, some technical and economic uncertainties such as rock density, uniaxial compressive strength, bit life and operating costs are considered in this system to evaluate the different optimization results. For this purpose, Vensim simulation software is utilized as a powerful dynamic tool for both modelling and optimizing under deterministic and uncertain conditions. It is concluded that an integrated optimization as opposed to the deterministic approach can be efficiently achieved. This however is dependent on the parameters that are considered as uncertainties.
