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21.
The combination of backstepping-based state-feedback control and flatness-based trajectory planning and feedforward control is considered for the design of an exponentially stabilizing tracking controller for a linear diffusion-convection-reaction system with spatially and temporally varying parameters and nonlinear boundary input. For this, in a first step the backstepping transformation is utilized to determine a state-feedback controller, which transforms the original distributed-parameter system into an appropriately chosen exponentially stable distributed-parameter target system of a significantly simpler structure. In a second step, the flatness property of the target system is exploited in order to determine the feedforward controller, which allows us to realize the tracking of suitably prescribed trajectories for the system output. This results in a systematic procedure for the design of an exponentially stabilizing tracking controller for the considered general linear diffusion-convection-reaction system with varying parameters, whose applicability and tracking performance is evaluated in simulation studies. 相似文献
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DWDM系统具有传输容量高、扩容简单和性能可靠等诸多优点,使得它在传送网中得到了广泛的应用.DWDM系统的商用使得对其各参数进行测试分析的各种方法层出不穷,文章围绕DWDM传输系统的光功率调试方面来进行讨论,从DWDM系统的功率平坦度出发,介绍了DWDM系统的光功率调试的相关指标,并在DWDM系统的端到端调试的准则下,详细分析了DWDM系统的光功率及平坦度调试方法,在此基础上对各个指标的调试作了探讨.最后以40波DWDM传输系统为例,详细介绍了DWDM系统光功率的计算及调试方法. 相似文献
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陶炳芳 《兰州工业高等专科学校学报》2012,(6):43-45
通过对人行道施工过程中出现的质量缺陷的调查,分析得出了出现质量缺陷的主要因素,并制定了相应对策以提高人行道施工中的质量问题. 相似文献
25.
基于PLC的瓷砖平整度在线检测系统研究 总被引:2,自引:0,他引:2
为实现瓷砖平整度的自动在线检测及分级,设计了基于PLC、组态软件和激光位移传感器的瓷砖平整度实时检测分级系统。系统由传送、检测和分级三部分组成。该检测系统采用光学三角法检测技术,通过编码器及PLC的高速计数器功能对移动中的待检测瓷砖的采样位置进行精确定位,使用激光位移传感器对瓷砖表面进行信息采集,经AD转换后在PLC内部按照特定的算法进行平整度运算,以PLC为核心实现瓷砖的分级处理和对设备的整体控制。实验表明该检测系统高效、稳定、可靠。瓷砖平整度检测精度为±0.1 mm,多次同方向检测精度为±0.05 mm,检测速度为每分钟40片,检测准确度可达到95%以上,适用于当前瓷砖生产过程的质量控制。 相似文献
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介绍了宝钢5m宽厚板轧机工作辊的弯辊/平衡系统,对这一系统的功能,机械、液压设备,压力补偿控制原理,闭环控制系统,参考值,板形及平直度控制,错误及警告等内容做了阐述,着重分析了弯辊系统的压力补偿控制原理。 相似文献
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During and after rolling or flattening of metal strips and plates the permissible deviations from flatness are described by the permissible absolute wave height and the flatness index. Both values can be determined on a measuring table while the material is not subjected to global tension. Because this procedure is expensive, time‐consuming and allows measurement only at discrete positions along the strip length, on‐line flatness measuring systems are used which can detect the distribution of longitudinal tensile stresses distributed across the strip width allowing for the calculation of the flatness index. This value does not always agree with the value obtained directly by measuring on the table even when the measurement of the longitudinal tensile stress distribution operates perfectly. It can be shown that the measurement of the tensile stress distribution does not give a direct indication on the wave height in the tension‐free state determined on the measuring table. To explain the relationship between tensile stress distribution in the strip and the flatness measurement on the measuring table, the buckling behavior is analysed both with and without dead load for simple symmetrical residual stress distributions resulting, e.g., from the rolling process. Based on the knowledge of the distribution of the longitudinal residual stresses across the strip width, the flatness index and the wave height can be determined by using a specialized finite element model. If the direct measurement is performed under action of dead load, large differences between the directly and indirectly obtained flatness index are observed. Below a certain limit of the intensity of the residual stress distribution the strips and plates lie flat on the measuring table. Above this limit the strip lying on the table exhibits post‐bucking deformations. In the latter case, the wave height increases with strip thickness and intensity of residual stresses. 相似文献
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Application of neural network interval regression method for minimum zone straightness and flatness 总被引:1,自引:0,他引:1
The goal of this paper is to develop an accurate, efficient, and robust algorithm for the minimum zone (MZ) straightness and flatness. In this paper, we use an interval bias adaptive linear neural network (NN) structure together with least mean squares (LMS) learning algorithm, and an appropriate cost function to carry out the interval regression analysis. From the results, we can see that both the straightness and flatness results from the interval regression method by NN can converge closer to the definition of the MZ straightness and flatness, respectively, than that of the least-squares (LSQ) method. The interval regression method by NN developed in this paper is applicable in the linear regression analysis that has a complicated constraint, and where the LSQ method cannot be used. 相似文献