一类广义非线性系统的鲁棒容错控制

介绍了一类自定义的广义非线性系统执行器和传感器故障部分进行限定条件下的鲁棒完整性容错控制器设计。     

基于ATIS下的鲁棒连续交通网络设计问题

考虑基于ATIS下的连续交通网络设计问题,假定网络上交通需求不确定,但属于一个有界椭球闭集,应用鲁棒优化的方法建立基于ATIS下的连续交通网络设计的鲁棒模型,然后应用需求生成的算法求解此模型,数值算例表明鲁棒设计方案更加可靠.     

基于ATIS下的鲁棒连续交通网络设计问题

考虑基于ATIS下的连续交通网络设计问题,假定网络上交通需求不确定,但属于一个有界椭球闭集,应用鲁棒优化的方法建立基于ATIS下的连续交通网络设计的鲁棒模型,然后应用需求生成的算法求解此模型,数值算例表明鲁棒设计方案更加可靠。     

不确定OD需求下混合交通网络设计的鲁棒优化模型

假定OD需求是不确定的,但它属于一个有界多面体,应用鲁棒优化的方法对不确定OD需求下混合网络设计问题进行了研究,建立了基于用户均衡的混合网络设计的极小极大模型,并采用需求生成的算法求解不确定OD需求下混合网络设计的鲁棒对应模型。数值算例的结果表明应用鲁棒优化方法得到的混合网络设计方案不仅更加符合实际,而且较传统确定性的混合网络设计方案具有更高的可靠性。     

不确定环境下集装箱码头的扰动管理

探讨了不确定环境下集装箱码头的扰动管理问题。对集装箱码头生产作业面临的不确定因素进行了分类和影响分析,提出了处理不确定因素的策略和扰动管理的体系框架;利用清晰集(凸集、区间等)、随机变量和模糊集等对集装箱码头面临的不确定因素进行了数学描述,在此基础上,阐述了鲁棒调度模型的建立和求解技术。     

不确定环境下集装箱码头的扰动管理

探讨了不确定环境下集装箱码头的扰动管理问题.对集装箱码头生产作业面临的不确定因素进行了分类和影响分析,提出了处理不确定因素的策略和扰动管理的体系框架;利用清晰集(凸集、区间等)、随机变量和模糊集等对集装箱码头面临的不确定因素进行了数学描述,在此基础上,阐述了鲁棒调度模型的建立和求解技术.     

不确定环境下集装箱码头的扰动管理

探讨了不确定环境下集装箱码头的扰动管理问题。对集装箱码头生产作业面临的不确定因素进行了分类和影响分析，提出了处理不确定因素的策略和扰动管理的体系框架；利用清晰集（凸集、区间等）、随机变量和模糊集等对集装箱码头面临的不确定因素进行了数学描述，在此基础上，阐述了鲁棒调度模型的建立和求解技术。     

基于鲁棒优化的集装箱码头连续泊位分配研究

合理的泊位调度计划能够提高码头资源的利用率,为解决不确定条件下的连续型泊位分配问题,对其建立了鲁棒优化模型,通过调节引入参数的值,可以根据不同的保守性得到不同代价下的鲁棒解。结果表明鲁棒解降低了船舶作业时间约束的保守性,提高了目标函数的最优性,因此可有效地降低决策的风险,在解决实际问题的过程中更为实用。     

需求不确定下闭环供应链生产计划优化研究

针对需求环境不确定的再制造闭环供应链,采用基于情景分析的鲁棒优化方法,建立基于物料需求计划的产品再制造闭环供应链生产计划运作鲁棒优化模型.制造商和供应商在整个供应链系统协调稳定运行的前提下,追求各自的期望利润最大化.并介绍了需求环境的变动给整个闭环供应链系统带来的影响,为企业生产计划的制订提供了解决方案.案例数值的结果也直接验证了该模型的Robust性.     

一类带有所有不确定项的中立时滞系统的H_∞控制问题

本文主要讨论了带有所有不确定项的线性时滞系统的鲁棒H∞控制问题.我们利用线性矩阵不等式技巧把它等价地转化为线性确定中立时滞系统的H∞控制问题.通过解线性矩阵不等式得到系统的鲁棒H∞控制律     

On the relationship between robustness to incomplete information and noise-independent selection in global games

This note demonstrates that a symmetric 3×3 supermodular game may fail to have any equilibrium robust to incomplete information. Since the global game solution in symmetric 3×3 supermodular games is known to be independent of the noise structure, this result implies that a noise-independent selection in global games may not be a robust equilibrium. Our proof reveals that the assumption in global games that the noise errors are independent of the state imposes a non-trivial restriction on incomplete information perturbations.     

The geometry of finite equilibrium datasets

We investigate the geometry of finite datasets defined by equilibrium prices, income distributions, and total resources. We show that the equilibrium condition imposes no restrictions if total resources are collinear, a property that is robust to small perturbations. We also show that the set of equilibrium datasets is pathconnected when the equilibrium condition does impose restrictions on datasets, as for example when total resources are widely noncollinear.     

Robust nonexistence of equilibrium with incomplete markets

We construct a pure exchange economy with spot and real security markets for which there does not exist a competitive equilibrium. Moreover, we show that the problem of nonexistence is robust to small perturbations of the endowments of the consumers. The result is driven by a lack of strict convexity of preferences.     

Housing prices and the business cycle: An empirical application to Hong Kong

This paper develops a two-agent, two-sector, open-economy DSGE model with a housing-market sector and a borrowing constraint. Contrary to standard conventions, domestic households are allowed to invest in foreign housing and vice versa. Using Bayesian methods, the model is applied to data for Hong Kong. We identify strong and robust housing wealth effects, and show that property prices are mainly driven by intratemporal preference perturbations rather than by disturbances in financial frictions or price mark up shocks. These disturbances also explain a non-negligible part of the volatility of consumption, GDP and employment.     

Robust Inference on Average Economic Growth*

We discuss a method to estimate the confidence bounds for average economic growth, which is robust to misspecification of the unit root property of a given time series. We derive asymptotic theory for the consequences of such misspecification. Our empirical method amounts to an implementation of the subsampling procedure advocated in Romano and Wolf (Econometrica, 2001, Vol. 69, p. 1283). Simulation evidence supports the theory and it also indicates the practical relevance of the subsampling method. We use quarterly postwar US industrial production for illustration and we show that non‐robust approaches rather lead to different conclusions on average economic growth than our robust approach.     

Robust optimal monetary policy in a forward‐looking model with parameter and shock uncertainty

This paper characterizes a robust optimal policy rule in a simple forward‐looking model, when the policymaker faces uncertainty about model parameters and shock processes. We show that the robust optimal policy rule is likely to involve a stronger response of the interest rate to fluctuations in inflation and the output gap than is the case in the absence of uncertainty. Thus parameter uncertainty alone does not necessarily justify a small response of monetary policy to perturbations. However, uncertainty may amplify the degree of ‘super‐inertia’ required by optimal monetary policy. We finally discuss the sensitivity of the results to alternative assumptions. Copyright © 2007 John Wiley & Sons, Ltd.     

DETERMINANTS OF INTRA-INDUSTRY TRADE: A SENSITIVITY ANALYSIS*

Abstract This paper examines the robustness of determinants of IIT to changes in the set of included variables and to measurement errors. On applying extreme bounds analysis (EBA) on Swedish IIT, it is found that most variables are sensitive to changes in the selected control variables. When examining the effects of errors of measurement and when only robust variables are included in the model, the estimated coefficients are bounded although they are unbounded when more variables are included. It is also found that the proxy-variables for product differentiation need to be of much higher quality than actually seems to be the case, if we are to ensure that the signs of the proxy-variables correspond to the signs of the ‘true’ variables.     

Robust prediction of domain compositions from uncertain data using isometric logratio transformations in a penalized multivariate Fay–Herriot model

Assessing regional population compositions is an important task in many research fields. Small area estimation with generalized linear mixed models marks a powerful tool for this purpose. However, the method has limitations in practice. When the data are subject to measurement errors, small area models produce inefficient or biased results since they cannot account for data uncertainty. This is particularly problematic for composition prediction, since generalized linear mixed models often rely on approximate likelihood inference. Obtained predictions are not reliable. We propose a robust multivariate Fay–Herriot model to solve these issues. It combines compositional data analysis with robust optimization theory. The nonlinear estimation of compositions is restated as a linear problem through isometric logratio transformations. Robust model parameter estimation is performed via penalized maximum likelihood. A robust best predictor is derived. Simulations are conducted to demonstrate the effectiveness of the approach. An application to alcohol consumption in Germany is provided.     

Nonparametric efficiency analysis: A multivariate conditional quantile approach

This paper focuses on nonparametric efficiency analysis based on robust estimation of partial frontiers in a complete multivariate setup (multiple inputs and multiple outputs). It introduces α-quantile efficiency scores. A nonparametric estimator is proposed achieving strong consistency and asymptotic normality. Then if α increases to one as a function of the sample size we recover the properties of the FDH estimator. But our estimator is more robust to the perturbations in data, since it attains a finite gross-error sensitivity. Environmental variables can be introduced to evaluate efficiencies and a consistent estimator is proposed. Numerical examples illustrate the usefulness of the approach.