基于关联规则与PLC的同步电机高精度转角自适应控制方法

常规的转角自适应控制方法未能与同步电机的实际运行数据精准结合,导致实际控制中精度不足,因此提出基于关联规则与PLC设计的同步电机高精度转角自适应控制方法。计算同步电机的增益效率,将结果加权处理,得到同步电机转角理想传动比的计算方法。建立关联数据库,基于关联规则优化转角控制增益系数。以适应性系数判断算法终止条件,建立自适应模型结构,得到同步电机中的转角质心偏离距离,设计转角模糊自适应算法。在对比试验中,试验组中适应性系数均值为0.48/0.92 μm,3个对照组的均值分别为0.27/0.82、0.42/0.57、0.26/0.86 μm。通过试验数据可知,基于关联规则与PLC的同步电机高精度转角自适应控制方法比常规算法更适应同步电机的实际运行,具备更高的精度控制效果。     

高风电渗透率下考虑需求侧管理策略的智能微电网调度方法

提出了一种高风电渗透率下考虑需求侧管理策略的智能微电网调度方法。首先,考虑经济、环境成本指标、清洁能源就地消纳量以及可中断负荷和可转移负荷策略,建立了多目标优化调度模型。然后,引入ε约束法生成Pareto前沿解集,利用归一化方法求出最优折衷解。最后,基于24节点配电系统对所提方法进行分析验证。算例结果表明:建立的多目标优化模型能够有效提升清洁能源的消纳率,提高调度方案经济性,同时有效降低发电污染排放。采用的需求侧管理策略能够有效平抑负荷波动,达到削峰填谷的目的。     

GM模型的几何性质及统计检验

以空间向量几何理论为基础，详细地分析了Ｇａｕｓｓ－Ｍａｒｋｏｖ线性模型的几何性质；在实现了模型图形化描述的基础上，利用各解向量的几何及统计性质构造出了不同情形下的统计检验方法和相应的检验统计量，为全面、深入地研究和灵活运用该模型提出了一种简洁直观的数学方法     

基于遗传算法的产品制造的优化调度

研究了企业产品制造的调度问题 ,并建立了调度的最小模型。引入效率函数 ,运用遗传退火进化算法实现了调度决策的优化 ;提出了将遗传退火算法和分派规则相结合的调度策略和动态编码的方法 ,放宽了约束条件 ,提高了搜索效率和速度 ,保证其全局收敛性。     

热轧钢卷强制冷却工艺的研究

试验研究了热轧钢卷的强制冷却工艺过程 ,探讨了钢卷强制冷却工艺参数对带钢表面质量、力学性能及板形等的影响 ,认为卷取后采用间断式强冷工艺可获得较好的表面质量、较均匀的力学性能 ,并能明显缩短钢卷库存时间     

Development of new device for measuring thermal stresses

In recent years, numerous analytical and experimental researches have been performed on the prediction of thermal stresses in mass concrete structures. However, due to the difficulty of the problem, limitations still exist for both analytical and experimental methods of measuring thermal stresses in mass concrete. In this research, a new experimental device measuring thermal stresses directly in a laboratory setting is developed. The equipment is located in a temperature chamber that follows the temperature history, which has been previously obtained from temperature distribution analyses. Thermal forces are measured continuously by two load cells in the device. The results show that the thermal stresses estimated by the newly developed device agree well with general stress variations in actual structures.     

Event-driven,pattern-based methodology for cost-effective development of standardized personal health devices

Experiences applying standards in personal health devices (PHDs) show an inherent trade-off between interoperability and costs (in terms of processing load and development time). Therefore, reducing hardware and software costs as well as time-to-market is crucial for standards adoption. The ISO/IEEE11073 PHD family of standards (also referred to as X73PHD) provides interoperable communication between PHDs and aggregators. Nevertheless, the responsibility of achieving inexpensive implementations of X73PHD in limited resource microcontrollers falls directly on the developer. Hence, the authors previously presented a methodology based on patterns to implement X73-compliant PHDs into devices with low-voltage low-power constraints. That version was based on multitasking, which required additional features and resources. This paper therefore presents an event-driven evolution of the patterns-based methodology for cost-effective development of standardized PHDs. The results of comparing between the two versions showed that the mean values of decrease in memory consumption and cycles of latency are 11.59% and 45.95%, respectively. In addition, several enhancements in terms of cost-effectiveness and development time can be derived from the new version of the methodology. Therefore, the new approach could help in producing cost-effective X73-compliant PHDs, which in turn could foster the adoption of standards.     

Credit rating with a monotonicity-constrained support vector machine model

Deciding whether borrowers can fulfill their obligations is a major issue for financial institutions, and while various credit rating models have been developed to help achieve this, they cannot reflect the domain knowledge of human experts. This paper proposes a new rating model based on a support vector machine with monotonicity constraints derived from the prior knowledge of financial experts. Experiments conducted on real-world data sets show that the proposed method, not only data driven but also domain knowledge oriented, can help correct the loss of monotonicity in data occurring during the collecting process, and performs better than the conventional counterpart.     

On the performance of economic model predictive control with self-tuning terminal cost

In this paper, we analyze the closed-loop performance of a recently introduced economic model predictive control (MPC) scheme with self-tuning terminal cost. To this end, we propose to use a generalized terminal region constraint instead of a generalized terminal equality constraint within the repeatedly solved optimization problem, which allows us to obtain improved closed-loop asymptotic average performance bounds. In particular, these bounds can be obtained a priori. We discuss how the necessary parameters for the generalized terminal region setting can be calculated, and we illustrate our findings with two numerical examples.     

结合相关规则和本体加权图的查询扩展

针对现有信息检索系统查询性能的不足,提出了一种结合相关规则和WordNet本体信息的查询扩展方法.该方法借助相关规则挖掘和WordNet本体信息构建加权词语关系图,并根据加权图的结构和权重信息计算扩展词的重要性.查询时,从这个图中取原查询词的最邻近词作为扩展词来源,选取其中权重最大的p个词返回并进行二次检索.在实现算法的基础上,通过Lucene全文检索器进行实验,将所得的结果值F1与其他算法的结果作比较.比较结果表明,该方法比不作扩展的检索有约16.93％的性能提升.