基于ＰＩＤ控制算法的直流微网容错控制方法研究

构建直流微网容错控制对象模型，调节直流微电网的输出回路参数；以输出功率、直流微网的 参考电压、弱电网下系统惯性响应特征等为约束参量，构建直流微网容错控制目标函数，在不同电网强度下 进行直流微网容错控制的参数自整定性调节，采用无功环比例积分控制方法进行直流微网容错寻优分析， 建立模糊 ＰＩＤ控制模型，采用变结构的模糊 ＰＩＤ控制方法进行直流微网容错控制过程中的自适应加权学习 和误差反馈调节，实现直流微网容错控制改进设计。仿真结果表明，采用该方法进行直流微网控制的容错 性能较好，输出稳定性较强，具有较好的直流微网输出增益。     

车载牵引变流系统故障诊断与容错控制综述

车载牵引变流系统作为高速列车的动力源,其安全可靠性对保障高速列车安全、高效、可靠的运行和维护至关重要。在非线性、强耦合和多工况等复杂条件和恶劣环境中长期运行,牵引变流系统中的各类部件都会出现不同程度的劣化失效,引发各类故障,给高速列车的安全运行带来极大挑战。为此,针对高速列车车载牵引变流系统功率器件、牵引控制单元、传感器和中间直流环节等故障率高的部件进行了故障诊断与容错控制方法的调研和总结,对比分析不同方法的研究思路和适用条件。最后,讨论车载牵引变流系统故障诊断与容错控制研究中亟待解决的问题,并对未来的研究做出展望。     

面向复合故障的牵引逆变器四桥臂容错控制

针对牵引变流器中NPC型三电平逆变器在一相或两相桥臂发生复合故障后的容错控制问题,在给出三电平逆变器四桥臂容错拓扑及其控制方式的基础上,通过分析逆变器主桥臂冗余矢量容错能力,归纳出复合故障类型,并就不同类型故障提出相冗余与矢量冗余相结合的容错控制策略,最终通过仿真建模对复合故障容错控制策略进行验证。仿真结果表明,三电平逆变器两相桥臂同时发生故障时可实现自动容错,故障后系统仍可全额或降额持续运行,验证了所提控制策略的有效性。     

基于NCAV和电路等效替换的PWM整流器容错控制系统

三相脉冲宽度调制(pulse width modulation,PWM)整流器因其具有可控的功率因数、网侧三相电流趋于正弦、直流侧电压稳定等优点,在电机控制、风力发电并网、柔性直流输电和微电网等领域得到广泛应用。为了提高三相PWM整流器可靠性,文中提出了一种PWM整流器容错控制系统,该系统结合了归一化电流平均值(normalised current average value,NCAV)故障检测法和基于电路等效替换的容错方法。该控制系统在功率开关管单管开路故障情况下能够实现故障检测和诊断,并进行快速的容错控制,从而减少单管开路故障对系统造成的影响,改善故障下三相电流波形,减小输出电压纹波,提升系统的整体性能和可靠性。通过仿真验证了该控制系统的有效性。     

基于信度融合和滑模控制的暂态电压扰动源容错性定位

提出了一种基于信度融合和滑模控制的含分布式电源(DG)智能配电网中实现暂态电压扰动源(TVDS)容错性自动定位方法。在基于网络化电能质量监测系统平台的TVDS容错性自动定位系统框架下,对其中关键功能模块的实现原理进行详细分析,包括基于电能质量监测点优化布置的电能质量动态状态估计、扰动方向判定信度影响因素分析及信度融合、DG接入对扰动方向判定影响规律分析与归纳。然后,提出一种基于滑模控制的TVDS容错性定位算法,实现综合考虑了扰动方向融合信度、DG接入方向误判校正的TVDS容错性自动定位。最后,通过IEEE 34节点含DG配电网络算例,分析验证了所提TVDS容错性定位方法的可行性和有效性。     

The principal factors affecting construction project overhead expenses: an exploratory factor analysis approach

Estimation is the first step in the project development process. Information technology provides an efficient platform for estimators to obtain quotations and specifications for their bid estimates. However, in practice, project overhead estimation relies heavily on the professional judgement and intuition of the estimators. This reduces the overall accuracy and reliability of the bid and a better understanding of the factors affecting project overheads is fundamental before any improved estimating methods can be devised. Unfortunately, the published literature on this topic is very limited. Using exploratory factor analysis, we aim to bridge the current knowledge gap by highlighting the principal factors affecting project overheads. Questionnaires detailing 27 variables were sent to quantity surveying managers of large contractors in Hong Kong. Seventy-nine valid responses were analysed by exploratory factor analysis. From the results, eight factors were extracted with their latent properties identified with reference to the expert opinions collected from telephone interviews. The findings clarify some misconceptions about the factors affecting project overheads and provide useful evidence for practitioners and researchers to understand project overheads. Estimators who address the identified factors when assessing future project overhead costs can improve the accuracy of their cost estimates and project budgets.     

Improved state space model predictive fault-tolerant control for injection molding batch processes with partial actuator faults using GA optimization

A novel model predictive fault-tolerant control (MPFTC) strategy adopting genetic algorithm (GA) is proposed for batch processes under the case of disturbances and partial actuator faults. Based on the extended state space model in which the tracking error is contained, there are more degrees of freedom provided for the controller design and better control performance is obtained. In order to enhance the control performance further, the GA is introduced to optimize the relevant weighting matrices in the cost function. The effectiveness of the proposed MPFTC approach is tested on the injection velocity regulation of the injection molding process.     

Indirect adaptive fuzzy fault-tolerant tracking control for MIMO nonlinear systems with actuator and sensor failures

In this paper, an active fuzzy fault tolerant tracking control (AFFTTC) scheme is developed for a class of multi-input multi-output (MIMO) unknown nonlinear systems in the presence of unknown actuator faults, sensor failures and external disturbance. The developed control scheme deals with four kinds of faults for both sensors and actuators. The bias, drift, and loss of accuracy additive faults are considered along with the loss of effectiveness multiplicative fault. A fuzzy adaptive controller based on back-stepping design is developed to deal with actuator failures and unknown system dynamics. However, an additional robust control term is added to deal with sensor faults, approximation errors, and external disturbances. Lyapunov theory is used to prove the stability of the closed loop system. Numerical simulations on a quadrotor are presented to show the effectiveness of the proposed approach.