基于GIS的灾害避难所适宜性评价及选址优化研究——以山东省日照市为例

作为应急管理的重点内容,灾害避难所的选址优化可为制定防灾减灾规划提供参考。以山东省日照市为例,基于GIS空间分析技术,采用起始点-目的地点(origin-destination,O-D)成本矩阵法、道路阻抗模型、Voronoi图算法和P-中值补充选址优化模型等方法,通过现在避难所的可达性分析、责任区评价及其人口配置缺口分析,多角度评价了日照市现有避难所的适宜性,并设计了3套避难所补充选址优化方案。结果表明:日照市道路交通可达性较高,各道路节点到其他所有节点平均车行时间为34.74~83.40 min,但现有避难所数量不足、空间分布过于集中,制约了现有避难所的可达性,不同辐射半径下,现有避难所可达范围分别仅占全市面积的12.60%、39.54%和78.69%。日照市现有避难所责任区内需跨区避难的乡镇和街道占比达18.52%,2种避难需求情景下,日照市人口配置缺口对应全市81.96%和15.91%的人口,现有避难所难以容纳。3套补充选址优化方案的近期规划方案中,建议新增高新区城市生态公园和开发区中心公园和奎山山地公园等8个公园绿地作为新建避难所。

具有执行器故障的网络控制系统的非脆弱保性能控制

对短时变时延下具有执行器故障的网络控制系统的鲁棒非脆弱保性能控制问题进行研究。为了降低保守性,利用标称点方法对系统进行建模,并结合时变故障矩阵与非脆弱控制,将连续时间系统模型转变为具有范数有界不确定参数的时变离散时间模型。根据Lyapunov对离散系统的稳定性判据以及线性矩阵不等式技术,给出保性能控制器的设计策略和相应的二次性能指标的求解方法,并通过算例验证了所提策略的正确性。

基于测试代价的三支邻域属性约简算法

针对粗糙集属性约简时很少考虑属性自身的测试代价等问题,提出了一种基于测试代价的三支邻域属性约简算法。算法根据各属性在邻域分辨矩阵中出现的频次和比例来计算属性重要性,并结合属性自身的测试代价来构造性价比指标,以此指导属性的甄选。三支决策方法被用于划分属性集,为属性的约简处理提供数据支撑。在7个UCI公共数据集上进行对比实验,结果表明,该算法可得到比对比算法更小的属性约简集合,在分类精度不降低的情况下,该算法具有更少的运行时间和更小的测试代价。基于财政收入的预测应用实例进一步证明了所提算法的有效性和实用性。

基于多目标函数的避洪转移安置方案优化

针对目前避洪转移方案仅考虑时间或距离成本最优导致部分安置点人数分配不合理的问题,从“安全第一、就近就便、平灾结合、利于管理”的避洪转移安置方案基本要求出发,首先对安置点的适用性、分布合理性及容量大小3个方面进行分析,依据“时间、距离、适宜度和安置容量”四因素初步筛选合适的安置点。然后通过路权函数建立避洪转移时间成本矩阵,以转移时间成本和安置点的优化分配为多目标函数确定避洪转移安置点的最优分配方案。最后以TOPSIS评价方法对避洪转移安置点分配的单目标方案与多目标方案进行对比分析。结果表明:多目标方案的相对接近度大于单目标方案,基于多目标函数确定的避洪转移安置分配方案更加合理。

基于路网数据的应急避难所可达性分析

应急避难所的可达性反映了当自然灾害和紧急情况来临时人们紧急避难规避风险的便利程度。通过收集长春市中心城区道路、应急避难所位置以及人口数据,基于ArcGIS桌面软件采用核密度分析、OD(origin-destination)成本矩阵等方法,分析长春市中心城区应急避难所的空间分布特征和可达性水平;对驾驶机动车和步行两种出行方式下不同时段到达避难所的人口进行了统计。结果表明,长春市中心城区的应急避难所设置较于集中,周边地区到应急避难所时间成本较高,区内少数人口受影响,应增设应急避难所。

基于LT码的分布式矩阵计算研究

在如今大数据和机器学习应用范围不断扩大的背景下,分布式计算系统成为处理庞大数据的必要工具。对于具有一定规模的计算集群,其性能会不可避免地受到系统噪声的影响,应考虑在分布式计算系统中借助编码技术来增强系统的鲁棒性。现有应用于分布式矩阵计算的编码方案多为固定速率编码,无法适应节点数量动态变化的实际情况。同时,由于部分任务有截止期限制,应在保证任务顺利完成的前提下尽可能地减少平均开销从而降低时延。针对上述问题,提出将LT码应用于雾计算场景下的分布式矩阵计算,设计Remo2算法。依托LT码的无速率特性自适应信道状态变化,通过合适的度分布函数设计以及双向切割、因子化度数的方法达到降低时延、增强分布式计算系统鲁棒性的预期效果。令k_(1)为A矩阵被切分后的子矩阵行值,k_(2)为B矩阵被切分后的子矩阵列值,实验结果表明,在k_(1)值固定的前置条件下,与FLT码及BDC-LT算法相比,Remo2算法的平均开销相对于前者稳定降低了33.3%,相对于后者减少了7.7%的冗余。此外,当k_(1)k_(2)大小的码长固定时,k_(1)、k_(2)的离散化程度越低,即limk_(1)-k_(2)→0,会带来更小的平均开销。

基于改进型M2PC控制方法的MC-PMSM控制系统

针对传统的模型预测控制(model predictive control,MPC)方法、调制模型预测控制(modulation MPC,M2PC)存在的问题,提出改进型M2PC方法,并用于矩阵变换器(matrix converter,MC)-永磁同步电机(permanent magnet synchronous motor,PMSM)系统控制。首先,给出了MC-PMSM的拓扑结构,分析了基于传统MPC、M2PC方法的MC-PMSM控制系统及其存在的问题;接着,提出了基于改进型M2PC方法,该方法不但能够固定开关频率,还能降低计算量和改善波形质量;最后,在RTDS平台上对MC-PMSM系统采用改进型M2PC方法进行仿真,并与采用传统的MPC、M2PC方法进行了比较。结果表明,所提改进型M2PC方法的控制性能优于传统的MPC、M2PC方法。

航空电子设备数字化柔性调测产线设计与实现

航空电子设备具有小批量多品种、高度综合化、功能指标多、产品组成复杂的特点,其调测数字化、自动化和柔性化非常重要。针对航空电子设备生产调测产线数字化、自动化和柔性化需求,提出一种数字化柔性调测产线建设方法,包括产线设计思路、软硬件设计等,同时,着重介绍了通用适配器设计、多通道射频矩阵设计、全自动装夹适配台设计等主要技术。该产线已应用于多型航空电子设备的调测生产,生产效率高、自动化程度高,具备可柔性换产能力,并缩短了产品的调测交付周期,降低了调测生产成本。

基于财务战略矩阵的家电制造企业财务优化研究——以浙江苏泊尔股份有限公司为例

以浙江苏泊尔股份有限公司(以下简称“苏泊尔”)为例,运用财务战略矩阵模型分析了家电制造企业的财务优化路径。通过构建和评价苏泊尔的财务战略矩阵图,展示了其在2018-2022年的财务波动情况,以及上述波动背后的内外部环境因素。基于分析结果,提出了相应的财务优化建议,旨在推动同类家电制造企业提升财务管理水平,实现降本增效。

Heuristic algorithm for RCPSP with the objective of minimizing activities' cost

Resource-constrained project scheduling problem（RCPSP） is an important problem in research on project management. But there has been little attention paid to the objective of minimizing activities＇ cost with the resource constraints that is a critical sub-problem in partner selection of construction supply chain management because the capacities of the renewable resources supplied by the partners will effect on the project scheduling. Its mathematic model is presented firstly, and analysis on the characteristic of the problem shows that the objective function is non-regular and the problem is NP-complete following which the basic idea for solution is clarified. Based on a definition of preposing activity cost matrix, a heuristic algorithm is brought forward. Analyses on the complexity of the heuristics and the result of numerical studies show that the heuristic algorithm is feasible and relatively effective.

Robust reliable guaranteed cost control for uncertain singular systems with time-delay

The robust reliable guaranteed cost control for uncertain singular delay systems with actuator failures and a given quadratic cost function is studied. The system under consideration involves constant time-delay and norm-bounded parameter uncertainties. The purpose is to design state feedback controllers which can tolerate actuator failure, such that the closed-loop system is stable, and the specified cost function has an upper bound for all admissible uncertainties. The sufficient conditions for the solvability of this problem are obtained by a linear matrix inequality （LMI） method. Furthermore, a numerical example is given to demonstrate the applicability of the proposed approach.

Non-fragile guaranteed cost control of discrete-time fuzzy bilinear system

This paper focuses on the problem of non-fragile guaranteed cost control for a class of T-S discrete-time fuzzy bilinear systems（DFBS）.Based on the parallel distributed compensation（PDC） approach,the sufficient conditions are derived such that the closed-loop system is asymptotically stable and the cost function value is no more than a certain upper bound in the presence of the additive controller gain perturbations.The non-fragile guaranteed cost controller can be obtained by solving a set of bilinear matrix inequalities（BMIs）.The Van de Vusse model is utilized to demonstrate the validity and effectiveness of the proposed approach.

An LMI Method to Robust Iterative Learning Fault-tolerant Guaranteed Cost Control for Batch Processes

Based on an equivalent two-dimensional Fornasini-Marchsini model for a batch process in industry, a closed-loop robust iterative learning fault-tolerant guaranteed cost control scheme is proposed for batch processes with actuator failures. This paper introduces relevant concepts of the fault-tolerant guaranteed cost control and formulates the robust iterative learning reliable guaranteed cost controller (ILRGCC). A significant advantage is that the proposed ILRGCC design method can be used for on-line optimization against batch-to-batch process uncertainties to realize robust tracking of set-point trajectory in time and batch-to-batch sequences. For the convenience of implementation, only measured output errors of current and previous cycles are used to design a synthetic controller for iterative learning control, consisting of dynamic output feedback plus feed-forward control. The proposed controller can not only guarantee the closed-loop convergency along time and cycle sequences but also satisfy the H∞performance level and a cost function with upper bounds for all admissible uncertainties and any actuator failures. Sufficient conditions for the controller solution are derived in terms of linear matrix inequalities (LMIs), and design procedures, which formulate a convex optimization problem with LMI constraints, are presented. An example of injection molding is given to illustrate the effectiveness and advantages of the ILRGCC design approach.

Delay-dependent guaranteed cost control for uncertain systems with both state and input delays

This paper considers the guaranteed cost control problem for a class of uncertain linear systems with both state and input delays. By representing the time-delay system in the descriptor system form and using a recent result on bounding of cross products of vectors, we obtain new delay-dependent sufficient conditions for the existence of the guaranteed cost controller in terms of linear matrix inequalities. Two examples are presented which show the effectiveness of our approach.

Optimal guaranteed cost control for fuzzy descriptor systems with time-varying delay

Based on the delay-independent rule, the problem of optimal guaranteed cost control for a class of Takagi-Sugeno （T-S） fuzzy descriptor systems with time-varying delay is studied. A linear quadratic cost function is considered as the performance index of the closed-loop system. Sufficient conditions for the existence of guaranteed cost controllers via state feedback are given in terms of linear matrix inequalities （LMIs）, and the design of an optimal guaranteed cost controller can be reduced to a convex optimization problem. It is shown that the designed controller not only guarantees the asymptotic stability of the closed-loop fuzzy descriptor delay system, but also provides an optimized upper bound of the guaranteed cost. At last, a numerical example is given to illustrate the effectiveness of the proposed method and the perfect performance of the optimal guaranteed cost controller.

Non-fragile guaranteed cost control for uncertain neutral large-scale interconnected systems

This paper focuses on the problem of non-fragile decentralized guaranteed cost control for uncertain neutral large-scale interconnected systems with time-varying delays in state,control input and interconnections.A novel scheme,viewing the interconnections with time-varying delays as effective information but not disturbances,is developed.Based on Lyapunov stability theory,using various techniques of decomposing and magnifying matrices,a design method of the non-fragile decentralized guaranteed cost controller for unperturbed neutral large-scale interconnected systems is proposed and the guaranteed cost is presented.The further results are derived for the uncertain case from the criterion of unperturbed neutral large-scale interconnected systems.Finally,an illustrative example shows that the results are significantly better than the existing results in the literatures.

Guaranteed cost sampled-data control for uncertain nonlinear time-varying delay system

The robust guaranteed cost sampled-data control was studied for a class of uncertain nonlinear systems with time-varying delay. The parameter uncertainties are time-varying norm-bounded and appear in both the state and the input control matrices. By applying an input delay approach, the system was transformed into a continuous time-delay system. Attention was focused on the design of a robust guaranteed cost sampled-data control law which guarantees that the closed-loop system is asymptotically stable and the quadratic performance index is less than a certain bound for all admissible uncertainties. By applying Lyapunov stability theory, the theorems were derived to provide sufficient conditions for the existence of robust guaranteed cost sampled-data control law in the form of linear matrix inequalities (LMIs), especially an optimal state-feedback guaranteed cost sampled-data control law which ensures the minimization of the guaranteed cost was given. The effectiveness of the proposed method was illustrated by a simulation example with the asymptotically stable curves of system state under the initial condition of x(0)=[0.679 6 0].

Guaranteed Cost Control for Uncertain Nonlinear Time-Delay Neutral Systems Based on T-S Fuzzy Model

The problem of guaranteed cost fuzzy controller is studied for a class of nonlinear time-delay neutral sys-tems with norm-bounded uncertainty based on T-S model. The sufficient conditions are first derived for the existenceof guaranteed cost fuzzy controllers. These sufficient conditions are equivalent to a kind of linear matrix inequalities.Furthermore, a convex optimization problem with LMI constraints is formulated to design the optimal guaranteedcost controller.

Suboptimal reliable guaranteed cost control for continuous-time systems with multi-criterion constraints

The suboptimal reliable guaranteed cost control （RGCC） with multi-criterion constraints is investigated for a class of uncertain continuous-time systems with sensor faults. A fauk model in sensors, which considers outage or partial degradation of sensors, is adopted. The influence of the disturbance on the quadratic stability of the closed-loop systems is analyzed. The reliable state-feedback controller is developed by a linear matrix inequalities （LMIs） approach, to minimize the upper bound of a quadratic cost fimction under the conditions that all the closed-loop poles be placed in a specified disk, and that the prescribed level of H∞ disturbance attenuation and the upper bound constraints of control inputs＇ magnitudes be guaranteed. Thus, with the above muki-criterion constraints, the resulting closed-loop system can provide satisfactory stability, transient property, a disturbance rejection level and minimized quadratic cost performance despite possible sensor faults.