三维自修正模糊控制器在重油加热炉控制中的应用

本文讨论了三维自修正模糊控制算法的基本思想及温度控制器的设计。仿真结果表明，三维自修正模糊控制系统在模型先配时的稳定性不仅优于常规PID控制系统，也优于常规二维模糊控制系统。     

解决零中频架构直流漂移的自校正方案

对零中频接收机中直流漂移的解决提出新的方案，利用通讯的等待时段检测，通过自校正电路扣除直流漂移量。这个方案不需要在信号通路上引入额外的电路模块，电路简单，引入的噪声小于0.1dB，对直流漂移抑制达到97％，芯片面积增加20％，附加功耗小于5μW。采用TSMC 0.25μm CMOS工艺参数进行HSPICE模拟仿真，结果证明了上述结论。     

压力传感器自学习校准系统的设计

提出了用计算机提高压力传感器性能和精度的方法,设计了硬件电路及软件。在对传感器修正方法的分析基础上,提出了一种综合修正压力传感器的温度误差和非线性误差的方法,并详细介绍了放大器自调零方法和系统自学习方法     

Students’ reflection on online self-correction and peer review to improve writing

Reflection is considered as a mental process of an individual’s internal problem-solving activity and rarely observed in face-to-face instruction. As a consequence, students have few opportunities to observe and learn from each other. This study aimed to arouse students’ reflection on both self-correction (one’s own problem-solving process in writing) and peer review (peers’ problem-solving process in writing) to improve their texts in an online system. A sample of 95 undergraduate students was recruited to write a reflective journal, which was analyzed by content analysis to compare their reflection on self-correction with peer review in writing. Results of this study revealed that reflecting on the differences between self-correction and peer review enabled students to monitor, evaluate, and adjust their writing processes in the pursuit of text improvement. In their reflective journals, students claimed that self-correction helped them detect grammatical errors (local revision) while peer review allowed them to view their own texts from others’ perspectives. Based on others’ perspectives, they could make further revisions on text development, organization, or style (global revision). Through reflection on self-correction and peer review, students were willing to provide further support to peers and learn from each other in the process of writing.     

Implementation of a MFAC based position sensorless drive for high speed BLDC motors with nonideal back EMF

In order to improve the reliability and reduce power consumption of the high speed BLDC motor system, this paper presents a model free adaptive control (MFAC) based position sensorless drive with only a dc-link current sensor. The initial commutation points are obtained by detecting the phase of EMF zero-crossing point and then delaying 30 electrical degrees. According to the commutation error caused by the low pass filter (LPF) and other factors, the relationship between commutation error angle and dc-link current is analyzed, a corresponding MFAC based control method is proposed, and the commutation error can be corrected by the controller in real time. Both the simulation and experimental results show that the proposed correction method can achieve ideal commutation effect within the entire operating speed range.     

Use Single－chip Computer to Realize Automatic Compensation for Optical Fiber Sensors

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Auto-compensation of nonlinear influence of environmental parameters on the sensor characteristics using neural networks

Usually the environmental parameters influence the sensor characteristics in a nonlinear manner. Therefore obtaining correct readout from a sensor under varying environmental conditions is a complex problem. In this paper we propose a neural network (NN)-based interface framework to automatically compensate for the nonlinear influence of the environmental temperature and the nonlinear-response characteristics of a capacitive pressure sensor (CPS) to provide correct readout. With extensive simulation studies we have shown that the NN-based inverse model of the CPS can estimate the applied pressure with a maximum error of +/- 1.0% for a wide temperature variation from 0 to 250 degrees C. A microcontroller unit-based implementation scheme is also proposed.     

一个实际温度控制系统自校正控制算法的设计

本文以染织厂染整车间匹布染色机染缸温度为被控对象,用动态预报最小方差为辩识方法组成的自校正控制系统,建立了被控对象和数学模型.在比较两种辩识方法的基础上,采用了动态预报方差最小方法作为该染整车间染缸温度被控对象的控制算法.实测了被控对象的动态特性,得到被控对象的时滞d(?)0,因此用 d=0时的被控对象数学模型和动态预报递推估计算法,设计了一种实用的自校正温度控制算法和软件,并应用于生产实践,从计算机打印出的工艺曲线与工艺要求的工艺曲绂相比较误差<±1℃,故所设计的自校正控制系统和算法是成功的,获得了较好的控制效果.     

Using a non-uniform self-selective coder for option pricing

We propose a non-uniform self-selective coder for option pricing. The system has one switch and four subsystems, which fits the need of advanced financial analysis. Using the system, we can obtain the following important information: (1) the most powerful explanatory variable, (2) the length of most representative sample period, and (3) the optimal updated model. In addition, with the non-uniform self-selective coder, the mean absolute errors have been decreased significantly.     

自纠正词对齐

词对齐是统计机器翻译系统的重要一环,但词对齐的获得往往基于序列模型的计算,而没有考虑语言的结构化信息及语言特征,从而造成词对齐中出现一些不符合语言特征的结果。文中提出一种词对齐的自纠正机制,以纠正词对齐中的错误部分。该机制使用一些语言学上的先验知识,对词对齐结果进行由粗颗粒度到细颗粒度的纠正。首先采用基于标点的方法对句对进行粗粒度化纠正,然后采用基于统计特征的方法对子句对进行细粒度化纠正。该自纠正过程不需要借助任何其他词对齐工具和新语料。实验结果显示,自纠正词对齐显著提高了词对齐的准确率,并提高了机器翻译的质量,其中粗粒度的纠正方法对翻译质量的提高最为显著,细粒度的纠正方法也提升了翻译质量,最终通过结合粗颗粒度和细颗粒度的纠正方法,使翻译结果相对基准系统取得了显著的提高。