需求不确定的电子供应链多目标鲁棒动态运作模型

建立了由多个供应商和多个不确定需求的顾客构成的多阶段供应链动态运作模型。供应链中的供应商可以通过电子市场也可以直接将多种产品供应给不同的顾客。采用已知概率的情景集合描述顾客不确定需求,利用基于情景分析的鲁棒优化方法,建立了供应链的运作模型。该模型为一个多目标动态规划问题,满足诸如尽可能达到顾客需求、系统的总成本最小、供应商的开工率不低于某一指定水平、对应于不确定需求的决策的鲁棒性等多个相互冲突目标。数值仿真结果表明,模型的解是最保守的,但却能够有效地保证供应链运作的鲁棒性。     

A robust control with a neural network structure for uncertain robot manipulator

A robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, and etc. Therefore, uncertainties are often nonlinear and time-varying. The neural network structure presents the bound function and does not need the concave property of the bound function. The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulator.     

A numerical investigation for robust stability of fractional-order uncertain systems

This study presents numerical methods for robust stability analysis of closed loop control systems with parameter uncertainty. Methods are based on scan sampling of interval characteristic polynomials from the hypercube of parameter space. Exposed-edge polynomial sampling is used to reduce the computational complexity of robust stability analysis. Computer experiments are used for demonstration of the proposed robust stability test procedures.     

一种改进的时滞不确定性系统鲁棒容错控制算法

研究了一类具有时滞不确定性系统的鲁棒容错控制问题,针对既有传感器失效,又有执行器失效的故障情形,通过引入一种无记忆的状态反馈控制器,基于Lyapunov稳定定理和运用线性矩阵不等式(LMI)的方法,给出了在传感器失效和执行器失效故障下具有鲁棒完整性的充分条件,并进行了证明。最后利用Matlab中的LMI工具箱进行了算例仿真,证实了这种设计方法的有效性和可行性,减少了当出现故障时需要先判断哪类故障的任务,为容错控制提供了便利。     

Artillery structural dynamic responses uncertain optimization based on robust Nash game method

Journal of Mechanical Science and Technology - To coordinate the contradiction between artillery launching performance indexes under parameter uncertainty, this paper proposes an artillery...     

A mathematical programming model for recycling network design under uncertainty: an interval-stochastic robust optimization model

The development of mathematical and optimization models for reverse supply network design has concerned considerable interest over the past decades. However, the uncertainties that are inherent in the network design and the complex interactions among various uncertain parameters are challenging the capabilities of these developed tools. The aim of this paper is to propose a new mathematical programming model for recycling network design in the iron and steel industry. The considered recycling network is multi-echelon, multi-facility, multi-product, and multi-supplier. Moreover, another objective of this research is to introduce an interval-stochastic robust optimization methodology to deal with various uncertainties in the proposed model. Computational experiments are provided to demonstrate the applicability of the proposed model in recycling network design.     

有决策时间窗匹配问题的决策优化支持模型

为了得到有决策时间窗限制的服务匹配决策问题的个体决策者的最优决策,定义了基于资源分布的时间窗匹配的个体决策问题,考虑了时间窗对决策者决策心理的影响,将问题的综合决策收益定义为期望收益与收益风险两个部分;基于时间窗内业务分布会发生变化的本质构建了考虑时间影响的期望收益模型;基于决策者在时间窗内对时间风险的3种态度,引入紧...     

不确定参数结构的区间优化方法

针对不确定参数结构,提出一种结构区间优化设计方法.由于区间优化问题一般要比确定性优化问题的求解复杂得多,因此,通过优化结构动力响应区间值的上界,将区间优化问题转化为近似的确定性优化问题.区间优化方法可以得到比传统确定性优化方法更多的优化信息.把该方法应用于典型桁架结构,优化结果表明,区间优化方法不仅能得到与传统优化方法大致相当的设计变量最优值,还能得到目标函数相应于设计变量最优值波动时的一个变化范围.     

Improved delay-range-dependent robust stability for uncertain systems with interval time-varying delay

This paper is concerned with the improved delay-range-dependent stability and robust stability criteria for linear systems with time-varying delay and norm-bounded uncertainties. In order to obtain much less conservative criteria, a Lyapunov-Krasovskii functional (LKF), which makes use of the information of both the lower and upper bounds of the interval time-varying delay, is proposed to derive new stability criteria. By using delayed decomposition approach (DDA), a tighter upper bound of the derivative of Lyapunov functional can be obtained, and thus the proposed criteria give results with less conservatism compared with some previous ones. The resulting criteria have advantages over some previous ones in that it involves fewer matrix variables but has less conservatism, which are established theoretically. We show, by four well known examples, that our result overcomes the previous allowable maximum admissible upper bound (MAUB) of the time-delay and it is less conservative than the previous results having a relatively small upper bound in the derivative of time delay.     

A moment-matching robust collaborative optimization method

Robust collaborative optimization (RCO) is a widely used approach to design multidisciplinary system under uncertainty. In most of the existing RCO frameworks, the mean of the state variable is considered as auxiliary design variable and the implicit uncertainty propagation method is employed for estimating their uncertainties (interval or standard deviation), which are then used to calculate uncertainties in the ending performances. However, as repeated calculation of the global sensitivity equations (GSE) is demanded during the optimization process of the existing approaches, it is typically very cumbersome or even impossible to obtain GSE for many practical engineering problems due to the non-smoothness and discontinuity of the black-box-type analysis models. To address this issue, a new RCO method is proposed in this paper, in which the standard deviation of the state variable is introduced as auxiliary design variable in addition to the mean. Accordingly, interdisciplinary compatibility constraint on the standard deviation of state variable is added to enhance the design compatibility between various disciplines. The effectiveness of the proposed method is demonstrated through two mathematical examples. The results generated by the conventional robust all-in-one (RAIO) approach are used as benchmarks for comparison. Our study shows that the optimal solutions produced by the proposed RCO method are highly close to those of RAIO while exhibiting good interdisciplinary compatibility.     

Identification of uncertain nonlinear systems for robust fuzzy control

In this paper, we consider fuzzy identification of uncertain nonlinear systems in Takagi-Sugeno (T-S) form for the purpose of robust fuzzy control design. The uncertain nonlinear system is represented using a fuzzy function having constant matrices and time varying uncertain matrices that describe the nominal model and the uncertainty in the nonlinear system respectively. The suggested method is based on linear programming approach and it comprises the identification of the nominal model and the bounds of the uncertain matrices and then expressing the uncertain matrices into uncertain norm bounded matrices accompanied by constant matrices. It has been observed that our method yields less conservative results than the other existing method proposed by S?krjanc et al. (2005) [11] and [12]. With the obtained fuzzy model, we showed the robust stability condition which provides a basis for different robust fuzzy control design. Finally, different simulation examples are presented for identification and control of uncertain nonlinear systems to illustrate the utility of our proposed identification method for robust fuzzy control.     

A robust design for a closed-loop supply chain network under an uncertain environment

This paper presents a robust design for a multi-product, multi-echelon, closed-loop logistic network model in an uncertain environment. The model includes a general network structure considering both forward and reverse processes that can be used in various industries, such as electronics, digital equipment, and vehicles. Because logistic network design is a time consuming and costly project as well as a strategic and sensitive decision (i.e. the change of such decision is difficult in the future), a robust optimisation approach is adopted to cope with the uncertainty of demand and the return rate described by a finite set of possible scenarios. Hence, to obtain robust solutions with better time, the scenario relaxation algorithm is employed for the proposed model. Numerical examples and a sensitivity analysis are presented to demonstrate the significance and applicability of the presented model. It is shown that solutions resulted from the suggested approach insure more situations, especially in worst case ones. The results show that although the profit values of the robust configuration are less than the deterministic configuration, the robust configuration is more reliable than the deterministic one because the deterministic configuration is infeasible under some demand and return rates (i.e. in the worst cases). Moreover, the results show the computing time superiority of the algorithm compared to the extensive form model as well as optimality of the resulted solutions.     

一类不确定性时滞系统的鲁棒控制器设计

本文讨论了一类非匹配时滞系统的鲁棒自适应控制和非线性控制问题.所讨论系统包含时滞及不确定性扰动项,且扰动项关于具有未知增益的高阶多项式函数有界而不是关于线性函数有界.利用Lyapunov-Krasovskii方法提出了保证系统渐近稳定的自适应控制器设计方法,相应的控制器是时滞依赖的.并利用Razumikhin引理给出了能使系统一致最终有界稳定的时滞独立的控制器设计方法.     

A delay decomposition approach to robust stability analysis of uncertain systems with time-varying delay

This paper is concerned with delay-dependent robust stability for uncertain systems with time-varying delays. The proposed method employs a suitable Lyapunov-Krasovskii's functional for new augmented system. Then, based on the Lyapunov method, a delay-dependent robust criterion is devised by taking the relationship between the terms in the Leibniz-Newton formula into account. By developing a delay decomposition approach, the information of the delayed plant states can be taken into full consideration, and new delay-dependent sufficient stability criteria are obtained in terms of linear matrix inequalities (LMIs) which can be easily solved by various optimization algorithms. Numerical examples are included to show that the proposed method is effective and can provide less conservative results.     

不确定线性系统鲁棒跟踪控制器的优化设计

基于优化二次型性能指标,以MATLAB为工具对具有乘性不确定线性系统的鲁棒跟踪控制器的优化设计问题进行研究.以一实例来说明鲁棒跟踪控制器具体的设计方法,给出该不确定系统鲁棒跟踪控制器的参数及系统的跟踪轨迹曲线.结果表明,所设计的鲁棒跟踪控制器能有效的跟踪给定,所提出的设计方法是有效的.     

A robust approach to edge detection of scanned point data

In reverse engineering, segmentation is used to divide a point data set into subsequent regions according to its shape. It is vital for interpretation of discrete scanned data since surface reconstruction can be accomplished one-by-one on a given region. Edge detection is crucial to the segmentation process. The level of edge detection depends on the complexity of the part, and it determines the eventual success or failure of the reverse engineering (RE) process. This paper proposes a novel approach to the edge detection of 3D points based on a region growing technique. The proposed algorithm consists of two parts. First, polygonal meshes are generated to the scanned point data using the Delaunay triangulation algorithm. Second, the normal vector and the area of a polygonal mesh are checked to find boundary meshes using cost criteria (angle criterion and area criterion) based upon a region growing technique. The region growing technique aggregates meshes into a region until the area of aggregated meshes reaches an area threshold from a series of seed meshes. The proposed edge detection method is found to be effective when compared with other methods.     

A robust single row facility layout problem with fuzzy random variables

The facility layout problem is the optimal arrangement of facilities in the plant area. Based on layout configurations, there are several types of the facility layout problem. The single row facility layout problem (SRFLP) is one them in which facilities have to be placed along a line. Although there are exact approaches, based on the integer programming model for solving SRFLP, a huge number of variables and constraints should be used in this model. This paper presents a new exact method to SRFLP based on a new class of variables and an extended branch and bound method (B&B). First, the SRFLP is formulated by new decision variables. To solve it, a new branching scheme for B&B algorithm is presented. Subsequently, we introduce a fuzzy robust single row facility layout problem (FRSRFLP) and solve it by a real expected value method and a fuzzy stochastic chance-constrained programming based on possibility and necessity measures together with an extended B&B method. Furthermore, the proposed methods are applied for solving some benchmark problems to show their efficiency.     

Improved results on delay-interval-dependent robust stability criteria for uncertain neutral-type systems with time-varying delays

In this paper, we consider the problem of delay-interval-dependent robust stability and stabilization of a class of linear uncertain neutral-type systems with time-varying delay. By constructing a candidate Lyapunov–Krasovskii functional (LKF), that takes into account the delay-range information appropriately, less conservative robust stability criteria are proposed in terms of linear matrix inequalities (LMIs) to compute the maximum allowable upper bounds (MAUB) for the delay-interval within which the uncertain neutral-type system under consideration remains asymptotically stable. The verifiable stabilizability conditions and memoryless state feedback control design are stated. Finally, numerical examples are also designated to demonstrate the effectiveness and reduced conservatism of the developed results.