管道清管器运行速度控制技术研究进展

随着对管道安全问题和降本增效理念的逐步重视，管道清管操作已成为全世界油气管道运行中必不可少的作业规程，清管器的运行速度是需要重点控制的参数之一，当其处于合理区间内时（原油管道1~5m/s，天然气管道2~7m/s），清管效果最佳。本文基于对管道清管数学模型的研究，首先论述了不同的被动控制方法，认为该方法较为灵活，应用广泛，对不同入口条件下清管器速度的准确计算是能否控制清管器速度处于合理区间的关键；然后对不同的主动控制方法进行了研究，研究表明：射流清管器速度控制的核心是旁通率的优选，其依赖于压降系数、皮碗与管壁间摩擦力的准确计算，建立简便可靠的摩擦力工程计算模型将有助于射流清管技术应用的进一步推广；最终本文对清管器智能调速技术进行综述和展望，指出发展稳定可靠的国产智能调速技术是未来重点研究方向。     

某两自由度弹药提升装置的建模、实验及仿真研究

弹药自动装填系统的研究已经成为火炮武器平台中机械系统设计的关键和难点,基于一种两自由度弹药提升装置,并根据该装置的工作原理构造数学模型,搭建实验平台,建立PID控制回路,同时创建该模型的虚拟样机模型,使用动力学仿真软件Recurdyn和Matlab/Simulink进行联合仿真,并通过实验与仿真的数据进行对比,验证该装置的可行性和所采用控制的有效性。     

A Student's t-based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results.     

Friction compensation controller for load varying machine tool feed drive

The load applied to a machine tool feed drive changes during the machining process as material is removed. This load change alters the Coulomb friction of the feed drive. Because Coulomb friction accounts for a large part of the total friction the friction compensation control accuracy of the feed drives is limited if this nonlinear change in the applied load is not considered. This paper presents a new friction compensation method that estimates the machine tool load in real time and considers its effect on friction characteristics. A friction observer based on a Kalman filter with load estimation is proposed for friction compensation control considering the applied load change. A specially designed feed drive testbed that enables the applied load to be modified easily was constructed for experimental verification. Control performance and friction estimation accuracy are demonstrated experimentally using the testbed.     

Control theory for stochastic distributed parameter systems,an engineering perspective

The main purpose of this paper is to survey some recent progresses on control theory for stochastic distributed parameter systems, i.e., systems governed by stochastic differential equations in infinite dimensions, typically by stochastic partial differential equations. We will explain the new phenomenon and difficulties in the study of controllability and optimal control problems for one dimensional stochastic parabolic equations and stochastic hyperbolic equations. In particular, we shall see that both the formulation of corresponding stochastic control problems and the tools to solve them may differ considerably from their deterministic/finite-dimensional counterparts. More importantly, one has to develop new tools, say, the stochastic transposition method introduced in our previous works, to solve some problems in this field.     

Adaptive actuator failure compensation design for unknown chaotic multi‐input systems

In this paper, an adaptive control approach is designed for compensating the faults in the actuators of chaotic systems and maintaining the acceptable system stability. We propose a state‐feedback model reference adaptive control scheme for unknown chaotic multi‐input systems. Only the dimensions of the chaotic systems are required to be known. Based on Lyapunov stability theory, new adaptive control laws are synthesized to accommodate actuator failures and system nonlinearities. An illustrative example is studied. The simulation results show the effectiveness of the design method. Copyright © 2014 John Wiley & Sons, Ltd.     

A novel quasi-oppositional harmony search algorithm and fuzzy logic controller for frequency stabilization of an isolated hybrid power system

The intermittent wind power in isolated hybrid distributed generation (IHDG) may cause serious problems associated with frequency (f) and power (P) fluctuation. Energy storage devices such as battery, super capacitor, and superconducting magnetic energy storage (SMES) may be used to reduce these fluctuations associated with f and P. This paper presents a study of IHDG power system for improving both f and P deviation profiles with the help of SMES. The studied IHDG power system is consisted of wind turbine generator and diesel engine generator. Both f and P control problems of the studied power system model are addressed in presence or absence of SMES. Fuzzy logic based proportional–integral–derivative (PID) controller with SMES is used for the purpose of minimization of f and P deviations. The different tunable parameters of the PID controller and those of the SMES are tuned by a novel quasi-oppositional harmony search algorithm. Performance study of the IHDG power system model is carried out under different perturbation conditions. The results demonstrate minimum f and P deviations may be achieved by using the proposed fuzzy logic based PID controller along with SMES.     

核算前移在冶炼企业优化成本控制中的应用

针对国际黄金价格的走低,黄金冶炼企业如何在激烈的市场竞争中寻求更大的利润空间,优化成本控制显得尤为重要。以某冶炼厂为例,阐述核算前移在优化企业成本控制中的应用,以达到降本增效的目的,实现企业利润的最大化。     

基于滑模的运载器主动段俯仰通道姿控系统设计

与传统比例-积分-微分（PID）控制方法相比，滑模控制（SMC）方法可以比较容易地将不确定性纳入控制器设计中，从而增强系统的鲁棒性。探索了SMC技术在运载器主动段姿态控制中的工程应用，首先通过分析基于趋近律的SMC系统，提出了降低不连续切换项系数的需求，然后研究了基于干扰上界的SMC方法。三通道小偏差仿真结果验证了两种方法的控制效果，表明第2种控制器的鲁棒性更好，稳态误差小，同时发动机喷管摆角需求较小。     

泛在电力物联网在北京经济技术开发区的应用探索

泛在电力物联网是物联网在电力领域的具体体现，建设泛在电力物联网是推进"三型两网"建设的关键环节，也是实现能源转型的必要手段。阐述了泛在电力物联网的定义，从供电公司角度出发，根据北京经济技术开发区实际情况，讨论了依托地区特点的泛在电力物联网实施策略和实际应用场景，分析了可能遇到的问题。得出结论：随着泛在电力物联网的深入建设，供电公司能够为电力客户提供多元化服务，提高客户满意度；地市供电公司能够依托泛在电力物联网开展更多电力相关业务；泛在电力物联网的安全性、实用性、有效性是发展面临的首要问题。