Implementation of dynamic matrix control on field programmable gate array

High performance computer is often required by model predictive control (MPC) systems due to the heavy online computation burden. To extend MPC to more application cases with low-cost computation facilities, the implementation of MPC controller on field programmable gate array (FPGA) system is studied. For the dynamic matrix control (DMC) algorithm, the main design idea and the implemental strategy of DMC controller are introduced based on a FPGA’s embedded system. The performance tests show that both the computation efficiency and the accuracy of the proposed controller can be satisfied due to the parallel computing capability of FPGA.     

Soft-Sensing Method with Online Correction Based on Semi-Supervised Learning

Soft sensing has been widely used in chemical industry to build an online monitor of the variables which are unmeasurable online or measurable online but with a high cost. One inherent difficulty is insufficiency of the training samples because the labeled data are limited. Besides, the traditional soft-sensing structure has no online correction mechanism. The forecasting result may be incorrect if the working condition is changed. In this work, a semi-supervised learning(SSL) method is proposed to build the soft-sensing model by use of the unlabeled data. Meanwhile, an online correction mechanism is proposed to establish a soft-sensing approach. The mechanism estimates the input variables at each step by a prediction model and calibrates the output variables by a compensation model. The experimental results show that the proposed method has better prediction accuracy and generalization ability than other approaches.     

HX_D2型电力机车新型重联渡板设计

针对目前国内线路上运行的电力机车使用的重联渡板的缺点,设计了适用于HXD2型电力机车使用的新型重联渡板装置,新型重联渡板核心部分采用可伸缩并可以自动复位的活动机构,解决了电力机车重联渡板碰撞变形等问题,同时提升了重联渡板的安全性及美观性。     

现代雷达对抗仿真系统的设计思想

雷达对抗仿真系统主要用于鉴定雷达对抗系统和设备的性能,为技术改进和选取技术指标提供科学依据。在积累的雷达电子对抗试验经验和学习的先进试验方法的基础上,提出了用于试验鉴定的现代雷达对抗仿真系统的设计思想。给出仿真系统框图和各主要部分功能,为了试验方便,在设置环境参数时提出了静态模式和动态模式,并对部分关键技术给出了解决办法。     

A Short-Term Traffic Flow Forecasting Method and Its Applications

Short-term forecast of urban traffic flow is very important to intelligent transportation. Although the conventional methods have some advantages, to some extent, in improving the traffic forecast’s precision, it is still hard to achieve high accuracy. In this paper, we propose a short-term traffic flow forecasting method, which is based on the hybrid particle swarm optimization-neural network(HPSO-NN) with error compensation mechanism.In HPSO-NN, the hybrid PSO algorithm is employed to train the structures and parameters of the feed-forward advanced neural network, while the error compensation mechanism is employed to improve the accuracy. HPSONN is used to forecast the vehicle velocity in Shanghai North-South Viaduct. Experimental results show that the HPSO-NN, compared with the auto-regressive and moving average(ARMA) model, can forecast traffic flow with a higher accuracy. What’s more, we have also found that HPSO-NN with error compensation mechanism has better performance than that of HPSO-NN alone.     

基于安全的公路功能分类探讨

公路功能分类和通行能力直接相关,干线公路要保证大通行能力,地方公路要便利,集散公路既要有一定的通行能力又要有一定的便利性,不同功能的公路的设计特征因此而有所不同。不同公路功能分类的公路设计特征、交通特征不同,其安全性也必然不同。我国公路考虑安全如何进行功能分类?本文通过归纳、总结国内外在公路功能分类、公路设计、公路安全计划等方面的实践经验以及相关研究成果,初步分析了我国公路分类存在的问题,探讨了公路功能分类和安全的关系,提出我国考虑交通安全的理想的公路功能分类,以及相关的研究、工作的建议。