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parameter uncertainty in CGE Modeling of the Macroeconomic Impact of Carbon Reduction in China

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Tsinghua Science and Technology 2006年第5期11卷 617-624页

作者：王灿陈吉宁 Department of Environmental Science and Engineering Tsinghua University

Formal methods are used to characterize the uncertainty in the computable general equilibrium （CGE） model outputs to assess the use of the CGE model of China （integrated energy-economyenvironment dynamic CGE, TEDCGE） for carbon tax policy issues. Monte Carlo experiment was used for the parameter uncertainty propagation and unconditional sensitivity analysis, using the variance of the conditional expectation （VCE） as the importance index to identify critical uncertainties. The results illustrate the statistical characteristics of TEDCGE outputs and sensitivities of the TEDCGE outputs to 50 uncertain elasticities. The results show that the carbon tax level for a predefined emission reduction goal is quite sensitive to both capital-energy substitution elasticity and inter-fuel substitution elasticity in the production function, while the key parameter for the GDP reduction rate was only the inter-fuel substitution elasticity. Among the various sectors, heavy industry and electricity are most vitally affected by a carbon tax.

关键词： parameter uncertainty unconditional sensitivity analysis computable general equilibrium carbon tax mitigation

Robust sliding mode control for fractional-order chaotic economical system with parameter uncertainty and external disturbance

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Chinese Physics B 2015年第3期24卷 101-106页

作者：周柯王智慧高立克孙跃马铁东 Electric Power Research Institute Guangxi Power Grid Corporation College of Automation Chongqing University

This paper presents a modified sliding mode control for fractional-order chaotic economical systems with parameter uncertainty and external disturbance. By constructing the suitable sliding mode surface with fractional-order integral, the effective sliding mode controller is designed to realize the asymptotical stability of fractional-order chaotic economical systems. Comparing with the existing results, the main results in this paper are more practical and rigorous. Simulation results show the effectiveness and feasibility of the proposed sliding mode control method.

关键词： fractional-order chaotic systems economical system sliding mode control parameter uncertainty

Robust distributed control of robot formations with parameter uncertainty

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控制理论与应用（英文版） 2011年第4期9卷 513-520页

作者： Huang HUANG Qinghe WU Di YU Beijing Institute of Control Engineering and Science and Technology on Space Intelligent Control Laboratory Beijing 100190 China School of Automation Beijing Institute of Technology B eijing 100081 China

This paper discusses robot formations in a distributed framework. The most important contribution is the incorporation of robustness into robot formation systems. When robots carry out tasks in a poor environment, the parameters in their models fluctuate around the nominal values, which may destroy the stability of the formation system. By modeling the group of robots as an interconnected system, we aim to develop a set of robust distributed controllers such that the overall system is robust to external disturbance as well as parameter uncertainty. Based on the graph rigidity theory, we also consider the rotation of a formation that plays an important role in real-time applications. Both simulations and real-time experiments are carried out to validate the effectiveness of the proposed framework.

关键词： Robots formation Distributed control parameter uncertainty LMI

Portfolio Choice under the Mean-Variance Model with parameter uncertainty

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Journal of Donghua University(English Edition) 2015年第3期32卷 498-503页

作者：何朝林许倩 School of Management Engineering Anhui Polytechnic University

Assuming the investor is uncertainty-aversion,the multiprior approach is applied to studying the problem of portfolio choice under the uncertainty about the expected return of risky asset based on the mean-variance model. By introducing a set of constraint constants to measure uncertainty degree of the estimated expected return,it built the max-min model of multi-prior portfolio,and utilized the Lagrange method to obtain the closed-form solution of the model,which was compared with the mean-variance model and the minimum-variance model; then,an empirical study was done based on the monthly returns over the period June 2011 to May 2014 of eight kinds of stocks in Shanghai Exchange 50 Index. Results showed,the weight of multi-prior portfolio was a weighted average of the weight of mean-variance portfolio and that of minimumvariance portfolio; the steady of multi-prior portfolio was strengthened compared with the mean-variance portfolio; the performance of multi-prior portfolio was greater than that of minimum-variance portfolio. The study demonstrates that the investor can improve the steady of multi-prior portfolio as well as its performance for some appropriate constraint constants.

关键词： portfolio choice mean-variance model parameter uncertainty multi-prior approach constraint constant

Adaptive PI Control Based Stability Margin Configuration of Aircraft Control Systems with Unknown System parameters and Time Delay

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Journal of Systems Science & Complexity 2024年第4期37卷 1507-1525页

作者： ZHANG Zhibing ZHOU Dapeng WANG Yeguang GAO Wanxin ZHANG Yanjun AVIC Shenyang Aircraft Design and Research Institute Shenyang 110035China School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China

The stability margin is a vital indicator for assessing the safety level of aircraft control *** should maintain sufficient stability margin to ensure safety during flight,especially in the process of large maneuver *** stability margin is generally quantified by the Bode diagram,which strictly depends on the system parameters and the open-loop transfer ***,due to the uncertain flight environments,transmission delays of sensors and mode switchings,etc.,there exist large parameter and structure uncertainties in the aircraft control systems,which make it difficult to precisely configure the stability margin to the desired value by the usual control *** address this problem,an indirect adaptive control strategy is proposed in this paper,where an adaptive PI control law with the capability of self-configuration of stability margin is *** developed control law not only achieves stable time-varying command tracking in the time domain,but also is able to automatically configure the phase margin and gain margin in the frequency ***,the simulation of the one-degree-of-freedom roll rate control model of the air vehicle verifies the validity of the proposed control method.

关键词： Adaptive control aircraft control parameter uncertainty stability margin configuration

parameter estimation for building energy models using GRcGAN

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Building Simulation 2023年第4期16卷 629-639页

作者： Hansol Shin Cheol-Soo Park Department of Architecture and Architectural Engineering College of EngineeringSeoul National UniversitySeoul08826R.O.Korea Institute of Construction and Environmental Engineering Institute of Engineering ResearchCollege of EngineeringSeoul National UniversitySeoul08826R.O.Korea

parameter estimation methods can be classified into(1)manual(trial-and-error),(2)numerical optimization(optimization,sampling),(3)Bayesian inference(Bayes filter,Bayesian calibration),and(4)machine learning(generative model).Bayesian calibration has been widely used because it can capture stochastic nature of uncertain ***,the results of Bayesian calibration could be biased by(1)the prior distribution assumed by the expert’s subjective judgment;(2)the likelihood function that cannot always describe the true likelihood;and(3)the posterior distribution approximation method,such as the Markov Chain Monte Carlo,which requires significant computation *** overcome this,a new approach using a generator-regularized continuous conditional generative adversarial network(GRcGAN)is presented in this *** target parameters of the DOE reference building model were *** was trained to estimate uncertain parameters using simulated monthly electricity and gas *** can successfully estimate five uncertain parameters based on 1,000 training data *** proposed approach presents a potential for stochastic parameter estimation.

关键词： generative adversarial networks generative model parameter estimation inverse problem model calibration parameter uncertainty

A New Sensitivity Analysis Approach Using Conditional Nonlinear Optimal Perturbations and Its Preliminary Application

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Advances in Atmospheric Sciences 2023年第2期40卷 285-304页

作者： Qiujie REN Mu MU Guodong SUN Qiang WANG State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences Fudan UniversityShanghai 200438China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Marine Hazards Forecasting Ministry of Natural ResourcesHohai UniversityNanjing 210098China College of Oceanography Hohai UniversityNanjing 210098China

Simulations and predictions using numerical models show considerable uncertainties,and parameter uncertainty is one of the most important *** is impractical to improve the simulation and prediction abilities by reducing the uncertainties of all ***,identifying the sensitive parameters or parameter combinations is *** study proposes a novel approach:conditional nonlinear optimal perturbations sensitivity analysis(CNOPSA)*** CNOPSA method fully considers the nonlinear synergistic effects of parameters in the whole parameter space and quantitatively estimates the maximum effects of parameter uncertainties,prone to extreme *** of the analytical g-function test indicate that the CNOPSA method can effectively identify the sensitivity of *** results of the theoretical five-variable grassland ecosystem model show that the maximum influence of the simulated wilted biomass caused by parameter uncertainty can be estimated and computed by employing the CNOPSA *** identified sensitive parameters can easily change the simulation or prediction of the wilted biomass,which affects the transformation of the grassland state in the grassland *** variance-based approach may underestimate the parameter sensitivity because it only considers the influence of limited parameter samples from a statistical *** study verifies that the CNOPSA method is effective and feasible for exploring the important and sensitive physical parameters or parameter combinations in numerical models.

关键词： physical parameters parameter uncertainty sensitivity analysis nonlinear optimization land-surface process

Arctic warming trends and their uncertainties based on surface temperature reconstruction under different sea ice extent scenarios

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Advances in Climate Change Research 2023年第3期14卷 335-346页

作者： Zi-Chen LI Wen-Bin SUN Cai-Xia LIANG Xu-Huang XING Qing-Xiang LI School of Atmospheric Sciences and Key Laboratory of Tropical Atmosphere-Ocean System Ministry of EducationSUN Yat-sen UniversityZhuhai 519082China Hainan Provincial Meteorological Bureau Haikou 570203China Research Center for Ecology and Environment of Central Asia Chinese Academy of SciencesWulumuqi 830011China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082China

IPCC AR6 states that the neglect of recent rapid warming in the Arctic generally leads to an underestimate of global warming *** this study,by reconstructing the surface temperature(ST)datasets in the Arctic under different sea ice extent scenarios(Imax and Imin),we respectively evaluated the annual and seasonal warming trends and their uncertainties from 1900 to *** results show that the reconstructed datasets have a good representation of the ST change trends in the *** 1900e2020,the annual warming trends in the Arctic(0.17±0.031 and 0.14±0.025℃ per decade under the Imax and Imin reconstruction,respectively)are roughly 1.6e1.8 times the global mean warming trends(0.10±0.008 and 0.09±0.008℃ per decade).While in 1979e2020,the Arctic warming trends(0.66±0.100 and 0.55±0.080℃ per decade)increase to 3.1e3.5 times of the global warming trend(0.19±0.023 and 0.18±0.023℃ per decade)for Imax and Imin,respectively,indicating that the Arctic amplification effect has been significantly enhancing in recent *** the seasonal warming trends are closely related to cloud feedback mechanisms,atmospheric circulation,and ocean circulation,they are not sensitive to the different reconstruction scenarios.

关键词： Arctic warming Reconstruction parameter uncertainty Reconstruction uncertainty Sea ice extent uncertainty

Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach

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Journal of Oceanology and Limnology 2020年第5期38卷 1382-1393页

作者： GAO Yongli MU Mu ZHANG Kun Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of SciencesQingdao 266071China University of Chinese Academy of Sciences Beijing 100049China College of Science China University of Petroleum(East China)Qingdao 266580China Institute of Atmospheric Sciences Fudan UniversityShanghai 200433China Qingdao National Laboratory for Marine Science and Technology Qingdao 266237China Center for Ocean Mega-Science Chinese Academy of SciencesQingdao 266071China

parameter uncertainty is a primary source of uncertainty in ocean ecosystem *** deep chlorophyll maximum(DCM)is a ubiquitous ecological phenomenon in the *** a theoretical nutrients-phytoplankton model and the conditional nonlinear optimal perturbation approach related to parameters,we investigated the eff ects of parameter uncertainties on DCM ***,the sensitivity of single parameter was *** sensitivity ranking of 10 parameters was obtained by analyzing the top four specifi *** most sensitive parameter(background turbidity)aff ects the light supply for DCM formation,whereas the other three parameters(nutrient content of phytoplankton,nutrient recycling coeffi cient,and vertical turbulent diff usivity)control nutrient *** explore the interactions among diff erent parameters,the sensitivity of multiple parameters was further studied by examining combinations of four *** results show that background turbidity is replaced by the phytoplankton loss rate in the optimal parameter *** addition,we found that interactions among these parameters are responsible for such diff ***,we found that reducing the uncertainties of sensitive parameters could improve DCM simulations *** with the sensitive parameters identifi ed in the single parameter analysis,reducing parameter uncertainties in the optimal combination produced better model *** study shows the importance of nonlinear interactions among various parameters in identifying sensitive *** the future,the conditional nonlinear optimal perturbation approach related to parameters,especially optimal parameter combinations,is expected to greatly improve DCM simulations in complex ecosystem models.

关键词： deep chlorophyll maximum(DCM)simulation parameter uncertainty conditional nonlinear optimal perturbation related to parameters(CNOP-P) sensitivity