To deal with the inherent nonlinearity and open-loop instability of the electromagnetic suspension (EMS) system, a new nonlinear control method is proposed. The simulation results show that, for a PID controller, the overshoot of the system response to an airgap step disturbance is about 3 mm, and the transient time is 6 s; however, for the proposed nonlinear controller, there is no overshoot and transient time within 2 s. The proposed method has a faster response and stronger robustness. With a designed bi-DSP suspension controller, this nonlinear control method was implemented on the Shanghai Urban Maglev Test Line (SUMTL) to validate its effectiveness and feasibility.
The overall behavior of concrete depends on its meso structures such as aggregate shape, interface status, and mortar matrix
property. The two key meso structure characters of concrete, bond status of interface and nonlinear property of matrix, are
considered in focus. The variational structure principle is adopted to establish the macro-meso constitutive law of concrete.
Specially, a linear reference composite material is selected to make its effective behavior approach the nonlinear overall
behavior of concrete. And the overall property of linear reference composite can be estimated by classical estimation method
such as self-consistent estimates method and Mori-Tanaka method. This variational structure method involves an optimum problem
ultimately. Finally, the macro-meso constitutive law of concrete is established by optimizing the shear modulus of matrix
of the linear reference composite. By analyzing the constitutive relation of concrete established, we find that the brittleness
of concrete stems from the imperfect interface and the shear dilation property of concrete comes from the micro holes contained
in concrete.
Supported by the National Natural Science Foundation of China (Grant Nos. 50679022, 90510017, 50539090) and National Basic
Research Program of China (Grant No. 2007CB714104) 相似文献
The thermal stability of seven organically modified montmorillonites (‘organoclays’) has been investigated using differential thermal analysis, differential scanning calorimetry, and thermogravimetry in conjunction with X-ray diffractometry. Six organoclays were synthesised by replacing the interlayer inorganic cations, initially present, with quaternary phosphonium and ammonium surfactant cations. The samples modified with tetrabutylphosphonium (TBP), and butyltriphenylphosphonium (BTPP) ions have an appreciably higher thermal stability than the octadecyltrimethylammonium (ODTMA)-modified clays. Thus, in the case of TBP- and BTPP-modified montmorillonites, the onset temperature of decomposition is close to 300 °C. Samples modified with hexadecyltributylphosphonium (HDTBP) ions have a lower onset temperature of decomposition of 225 °C. In comparison, the onset temperature for ODTMA-montmorillonites (obtained at different concentrations of ODTMA-bromide) ranges from 158 to 222 °C, being highest where the concentration of intercalated surfactant is lowest. The onset temperature for a commercial alkylsilane-treated quaternary ammonium-modified organoclay (S-BEN N-400FP) is 207 °C. The basal spacing of the TBP- and BTPP-modified clays is 1.7–1.8 nm, indicating a monolayer arrangement of quaternary phosphonium ions in the interlayer space, while the value of 2.5 nm for HDTBP-montmorillonite indicates a more open structure. The ODTMA-modified samples have basal spacings ranging from 1.9 to 2.1 nm, indicative of a bilayer to pseudo-trilayer arrangement. The exceptionally high basal spacing of 3.4 nm for the S-BEN N-400FP organoclay might be due to interlayer penetration of organosilane hydrolysis products during synthesis. The thermal properties of organoclays are apparently related to the nature of the surfactants and their arrangement in the interlayer space of montmorillonite. 相似文献
Neural Processing Letters - In this article, the finite time (FT) synchronization problem of fractional order quaternion valued neural networks with time delay is investigated. Without separating... 相似文献
Information Systems Frontiers - System logs that trace system states and record valuable events comprise a significant component of any computer system in our daily life. Each log contains... 相似文献
Palmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition, and have achieved impressive results. However, the research on deep learning-based palmprint recognition and palm vein recognition is still very preliminary. In this paper, in order to investigate the problem of deep learning based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct performance evaluation of seventeen representative and classic convolutional neural networks (CNNs) on one 3D palmprint database, five 2D palmprint databases and two palm vein databases. A lot of experiments have been carried out in the conditions of different network structures, different learning rates, and different numbers of network layers. We have also conducted experiments on both separate data mode and mixed data mode. Experimental results show that these classic CNNs can achieve promising recognition results, and the recognition performance of recently proposed CNNs is better. Particularly, among classic CNNs, one of the recently proposed classic CNNs, i.e., EfficientNet achieves the best recognition accuracy. However, the recognition performance of classic CNNs is still slightly worse than that of some traditional recognition methods.
