需求分布不确定条件下的多周期库存鲁棒优化模型

在离散需求情景概率不确定的条件下, 建立基于最大最小方法的多周期库存鲁棒优化模型. 考虑需求分布分别隶属于区间和椭球不确定集两种情形, 运用对偶理论将多周期库存鲁棒优化模型转化为易于求解的凸规划问题. 数值结果表明, 与已知需求分布下的系统最优绩效相比, 采用鲁棒订货策略虽然会导致部分绩效损失, 但损失值很小, 表明基于鲁棒优化的多周期库存订货策略具有良好的鲁棒性, 能够有效抑制需求分布不确定性对库存运作绩效的影响.

     

基于鲁棒可靠性的不确定时滞系统最优H∞控制器设计

用区间变量描述控制系统参数的不确定性,提出了不确定时滞系统鲁棒H_∞控制的鲁棒可靠性方法,基于鲁棒可靠性的不确定时滞系统最优状态反馈H_∞控制器设计方法,将系统的最优控制器设计归结为基于线性矩阵不等式(LMI)的优化问题．所设计的控制器可以在满足对所有不确定性鲁棒可靠的前提条件下,具有最优的H_∞鲁棒性能,并能在控制系统的设计中综合考虑控制性能、控制代价和鲁棒可靠性．数值算例说明了所提方法的有效性和可行性．     

基于T-S模型的非线性系统非脆弱极小极大控制

研究一类非线性离散系统的鲁棒非脆弱极小极大控制问题.针对含有不确定项的非线性离散系统,构造T-S模型,引入参数不确定项,使得模糊模型能够更精确逼近原系统.考虑系统和控制器同时含有不确定性,利用线性矩阵不等式(LMI)处理方法和Lyapunov稳定性理论,设计鲁棒且非脆弱的控制器.考虑不确定性使得性能指标最大的情形,得到极小极大鲁棒非脆弱控制器存在的充分条件.引入凸优化算法,求解使闭环系统渐近稳定且性能指标上界最小的最优极小极大鲁棒控制器的参数.最后以著名的truck-trailer模型为例的仿真结果表明所设计的控制器具有良好的鲁棒性和非脆弱性.     

服务率不确定的单站点传送带给料加工站系统鲁棒优化控制

研究了服务率不确定情况下的单站点传送带给料加工站(CSPS)系统的鲁棒优化控制问题。在仅知服务率区间的条件下,以CSPS系统的前视距离作为控制变量,将鲁棒优化控制问题建模成不确定参数的半马尔可夫决策过程(SMDP)的极大极小优化问题,在状态相关的情况下,给出全局优化算法进行鲁棒控制策略求解。首先,运用遗传算法求解固定策略下的最差性能值;其次,根据求解得到的最差性能值,运用模拟退火算法求解最优鲁棒控制策略。仿真结果表明,服务率不确定的CSPS系统的最优鲁棒性能代价与服务率固定为区间中值系统的最优性能代价相差不大,并且随着不确定区间的缩小,两者的差值越小,说明了全局优化算法的有效性。     

不确定条件下控制分配问题的鲁棒优化方法

针对具有冗余执行机构的过驱动系统, 在考虑控制效率不确定性的条件下, 提出了一种基于鲁棒优化理论的控制分配算法. 研究了原始不确定鲁棒优化模型的建立和基于椭球不确定集的鲁棒对等式的转化问题, 并推广到可由锥二次不等式表示的不确定集的情况. 讨论了鲁棒优化控制分配算法的求解方法及其计算复杂度. 最后, 针对多操纵面飞机的最优控制分配问题与传统算法进行了仿真比较, 结果表明鲁棒优化算法能有效降低控制效率不确定性的影响, 使分配结果更为合理, 从而具有更好的鲁棒性, 同时能有效提高操纵面故障情况下闭环系统的控制重构能力, 很好地改善了飞控系统的性能.     

基于Prim-DMGA算法的闭环供应链网络鲁棒优化研究

针对不确定环境下的闭环供应链网络优化问题,在需求不确定及设施中断风险的条件下,基于鲁棒对等优化方法建立了一种以闭环供应链网络总成本最小为目标的鲁棒优化模型,以解决供应链网络中的不确定性问题,并提出了Prim-DMGA。首先基于Prim算法得到高质量的初始种群,其次让路径规划方案和设施选址方案在两层自适应GA的不断反馈中达到最优。实验结果表明,Prim-DMGA得到的目标函数值优于单层Prim-MGA与传统GA,且在求解大规模算例时,求解结果优于CPLEX软件。研究结论表明,Prim-DMGA能以较少的计算时间获得质量更优的解,鲁棒优化模型可以有效减少不确定因素带来的不利影响,提高闭环供应链网络的鲁棒性能。     

基于区间矩阵的四旋翼无人机鲁棒跟踪控制

针对飞行环境不断变化的四旋翼无人机轨迹跟踪问题,提出了基于区间矩阵的鲁棒跟踪控制策略.首先,将四旋翼无人机非线性动态模型解耦为外环位置控制系统和内环角度控制系统.接着,考虑到飞行环境变化引起的升力系数、中高速飞行下不可忽略的阻力系数等参数的不确定性,引入区间矩阵对内外环系统的系统参数进行描述,并对内外环控制系统设计鲁棒H_∞反馈控制策略来抑制有界外部扰动.然后,根据李雅普诺夫稳定性定理得到了使外环系统指数渐近稳定和内环系统鲁棒渐近稳定且均满足H_∞性能指标的LMI充分条件,同时,给出了控制器增益的求解方法.最后,仿真及实验结果结果验证了所提方法的鲁棒性、优越性和有效性.     

不确定旅行商问题的鲁棒模型与算法

考虑到不确定参数在旅行商问题(TSP)中广泛存在,在Bertsimas鲁棒离散优化理论的框架下,建立了不确定旅行商问题的鲁棒优化模型,并按转换规则将鲁棒模型转换为鲁棒对等模型。给出了一种求解旅行商问题的基于Prufer数编码的单亲遗传算法,与求解该类问题的传统遗传算法相比,该算法缩减了染色体长度,避免了传统交叉和变异操作破坏染色体可行解的缺陷。通过算例验证,表明该算法有较高的求解效率,所建立的鲁棒模型在不确定环境下能得到较好的鲁棒解。     

能效最优准则下的无人机中继系统的功率分配算法

由于无人机（Unmanned aerial vehicle,UAV）机动性好且部署简单,基于无人机中继的传输技术受到了广泛关注。功率作为通信系统的重要资源,其分配问题直接影响各条链路的性能和整个通信系统的能量效率。本文以莱斯衰落信道为背景,提出了一种在系统能效准则下的无人机中继通信系统的功率分配算法。首先在双跳放大转发（Amplify-and-forward,AF）中继传输模型的基础上建立功率分配的优化模型,将功率分配问题转化为求解最大系统能效的优化问题。在最优功率分配的求解过程中,先固定发射信号功率,获得波束形成优化方案;然后通过大信噪比区间近似,将非凸优化问题转化为凸优化问题;最后利用KKT（Karush-Kuhn-Tucker）条件,计算得出功率分配方案的闭式解。仿真实验表明,本文算法相对于迭代算法降低了算法复杂度。     

基于无人机基站的节能通信部署研究

为保证用户服务质量(Quality of Service, QoS),针对用户分布不均匀状态,解决无人机基站以最小发射功率覆盖相同数量用户问题,提出一种基于最小包围圆和K-means算法的无人机优化部署方法。利用贪心算法思想将部署问题解耦为垂直和水平放置问题,分别通过求解最优性确定无人机基站三维部署位置。利用聚类分析方法构建用户簇,采用最小包围圆思想对无人机基站水平位置进行优化;以最小化通信能耗为目标,建立无人机基站通信模型确定无人机最优飞行高度;联合两种优化方案确定三维部署位置。针对用户不同分布状态对无人机基站发射功率的仿真实验,验证了部署方法的有效性。     

A cross-layer communication module for the Internet of Things

The Internet of Things (IoT) is a novel networking paradigm which allows the communication among all sorts of physical objects over the Internet. The IoT defines a world-wide cyber-physical system with a plethora of applications in the fields of domotics, e-health, goods monitoring and logistics, among others. The use of cross-layer communication schemes to provide adaptive solutions for the IoT is motivated by the high heterogeneity in the hardware capabilities and the communication requirements among things. In this paper, a novel cross-layer module for the IoT is proposed to accurately capture both the high heterogeneity of the IoT and the impact of the Internet as part of the network architecture. The fundamental part of the module is a mathematical framework, which is developed to obtain the optimal routing paths and the communication parameters among things, by exploiting the interrelations among different layer functionalities in the IoT. Moreover, a cross-layer communication protocol is presented to implement this optimization framework in practical scenarios. The results show that the proposed solution can achieve a global communication optimum and outperforms existing layered solutions. The novel cross-layer module is a primary step towards providing efficient and reliable end-to-end communication in the IoT.     

Optimization of Communication Network Fault Identification Based on NB-IoT

The Internet of Things (IoT) has developed an industrial and medical application in dramatic growth in recent years. Narrow Band-Internet of Things (NB-IoT) is a wireless communication and low power wide area technology based on new IoT devices and enables various services to grow. NB-IoT communication significantly increases the power consumption of user equipment, computer capacity, and spectrum performance. Network communication is complex, and the amount of information these networks have made it extremely difficult to manage the transmissions. Since the communication network failure is inevitable, rapid detection, identification, and recovery are the most reliable; it is essential to the high-speed operation. Narrow Band-IoT (NB-IoT) networking technology has proposed the idea of detecting network communication fault. The NB-IoT technique can help save a lot of energy by significantly reducing the number of retransmission required. The proposed technology proves that this research is a powerful proposition for achieving the ideal energy potential. Performance analysis and simulation results show that the detection mechanism can improve transmission efficiency and effectively reduce network communication failures power consumption.     

物联网中可信控制技术研究

在物物通信和物联网技术的基础上综述了国内外物联网的发展现状,提出了物联网中无线传感器网络(WSN)与lnternet的互联融合模型.结合此模型,研究了其可信控制关键技术,包括可信路由技术、信任控制技术,以促进物联网在中国的安全发展.     

RETRACTED ARTICLE: Multimodal interface interaction design model based on dynamic augmented reality

New channels, new carriers continue to produce new data types, how to deal with complex and volatile multi-source data under IoT big data environment has become an important issue. Information perception is the basic content of the development of things, but also an important means to achieve information perception. Information interaction is the basic condition for the realization of Internet of things, but also the basic technology of interconnection. The information sensing of the Internet of Things is mainly the source of information provided by it, which is also the application base of the Internet of Things itself. To effectively process the IoT data, this paper proposes the multimodal intelligent data analyzing paradigm for Internet of things systems. Our proposed multiple game theory based data analyzing paradigm will guarantee the optimal combination of the mentioned model to construct the effect and robust analyzing pattern. We construct the optimal combination of Bayesian model, Decision Tree, Random Forest, Logistic Regression, SVM, Adaboost, Markov and Neural Network under the multiple game framework. Several new ideas are proposed to enhance the traditional Nash Equilibrium. Performance of the proposed method is validated through the simulation compared with the other state-of-the-art algorithms.

     

A multi-objective robust optimization approach based on Gaussian process model

The design and optimization of engineering products is usually multi-objective, constrained and has uncertainties in the inputs. It is of great importance for taking these uncertainties into consideration during the design process because these uncertainties can significantly degrade the performance of optimal solutions and even change the feasibility of obtained solutions. Most existing Multi-objective robust optimization (MORO) approaches rely on outer-inner nested optimization structures, where a large number of function evaluations is required. In this work, a MORO approach based on Gaussian process (GP) model is proposed to ease the computational burden of MORO under interval uncertainty. To consider the interpolation uncertainty introduced by GP model, an objective switching criterion is developed, which is according to whether the robust status of the individual can be changed because of the interpolation uncertainties from GP model or not. Six numerical and engineering cases with different degrees of difficulty are used to demonstrate the applicability and efficiency of the proposed approach. The objective and feasibility robustness of the obtained optimal solutions are verified via the design of experiment.     

物联网的军事应用研究

物联网被公认为是继计算机、互联网与移动通信网之后的世界信息产业第三次浪潮。在以高姿态进入人们视野的同时,物联网的应用成为万众瞩目的焦点。军事领域历来都是高新技术创新与应用的聚焦地,物联网带来的军事影响绝不亚于互联网,将触发军事变革的一次重新启动。文章从物联网的军事应用出发,分析了物联网在战场感知、作战指挥、装备管理、后勤保障等方面的应用,指出了物联网在军事应用中所面临的主要问题。     

Intelligent and trusted metaheuristic optimization model for reliable agricultural network

Artificial intelligence (AI) is gaining demanding growth in the field of smart cities, agriculture, food management, and weather forecasting due to the lack of computing power on sensing devices. The applications of artificial intelligence are integrated with various Internet of Things (IoT) and ubiquitous sensors for the improvement of the agriculture sector and to decrease its management cost. Due to the bounded resources of wireless technologies, most of the solutions are designed for efficient delivery of agriculture data to cloud systems, however, still optimizing the resources management and data load for forwarding nodes, especially those closest to edge boundaries is a challenging issue. Moreover, due to the collection of incorrect environmental data, the decision-making process leads to a decrease in the productivity of the optimization process. To overcome such issues, this work proposes a trustworthy and intelligent agricultural model that uses metaheuristic optimization to enhance resource management to address these problems. The proposed model approach employs the decision-making function to overcome information loss and inconsistency. Moreover, it builds trust in agricultural data collection by using secure IoT devices and facilitating reliable communication. In terms of performance metrics, the proposed model is simulated to assess its importance in comparison to state-of-the-art solutions. It not only collects updated data from agricultural land but also uses artificial intelligence's lightweight optimization technique to reduce the overheads on IoT devices. The experiment findings demonstrate the importance of the proposed model for resource monitoring and overheads on the IoT system.     

面向物联网的改进PBFT共识算法

随着物联网的发展,高效的共识算法是区块链技术应用于物联网的关键.针对实用拜占庭容错(practical Byzantine fault tolerance, PBFT)算法在物联网场景中通信次数多、未考虑共识功耗、共识时延高等问题,本文提出了一种基于二分K均值算法的改进PBFT共识算法(binary K-means practical Byzantine fault tolerance algorithm,BK-PBFT).首先,获取节点地理坐标并计算节点综合评价值,通过二分K均值算法将节点划分为一个双层多中心聚类集群.然后,先在下层集群再在上层集群对区块进行PBFT共识.最后,集群验证执行并存储区块,完成共识.此外,本文证明了当节点均匀分布在每个簇时算法通信次数可以达到最少,以及通信次数最少时的最优聚类数.分析与仿真结果表明,本文算法可以有效减少通信次数、降低共识功耗和共识时延.     

Simulation of art design of indoor furnishings based on FPGA and internet of things system

The Internet of Things (IoT) is fast becoming a business opportunity and home indoor design technology, and standards, mainly in wireless communication between everyday human life equipment and tools, in general, is known as the Internet of Things (IoT). The art design of products is behind the home indoor decor furnishing, and there is also service to appliances that connect to the entire home control system internet. This service allows users to decorate their home's indoor design while building an IoT and Field Programmable Gate Array (FPGA) environment. The smart home system has achieved great popularity in the past few decades because they improve the comfort and quality of life. Smartphones and microcontrollers using wireless communication technology, control, and integration of the characteristics of the control room furniture and Internet of Things (IOT) Internet Control smartphone applications intelligent home system, the sensor is triggered and intelligent Internet support. Cloud computing technology is embedded in the content of the smart home. A smart home is a platform that includes to build smart homes, automate, and provide an efficient, comfortable, safe, and convenient home environment. IoT, the detection information, a Radio Frequency Identification System (RFID), sensors, a global positioning system (GPS), the laser scanner, and other knowledge, such as infrared rays, is connected to the Internet.     

面向监测应用的物联网节点布局方法研究

针对物联网监测系统面临的高效监测质量与居高不下的监测成本的矛盾问题，提出综合考虑物联网规模、成本、综合代表性以及均衡度目标的节点选择与布局方案，构建了混合整数非线性多目标规划模型，通过遗传算法求得了节点的数量和布局方案，并且对节点的选择进行了评价。仿真结果表明，所建立的模型及其求解方法有助于缓解监测质量与成本之间的矛盾，对监测系统设计与物联网研究具有理论意义。