Adaptive boundary control for unstable parabolic PDEs—Part II: Estimation-based designs

The certainty equivalence approach to adaptive control is commonly used with two types of identifiers: passivity-based identifiers and swapping identifiers. The “passive” (also known as “observer-based”) approach is the prevalent identification technique in existing results on adaptive control for PDEs but has so far not been used in boundary control problems. The swapping approach, prevalent in finite-dimensional adaptive control is employed here for the first time in adaptive control of PDEs. For a class of unstable parabolic PDEs we prove a separation principle result for both the passive and swapping identifiers combined with the backstepping boundary controllers. The result is applicable in any dimension. For physical reasons we restrict our attention to dimensions no higher than three. The results of the paper are illustrated by simulations.     

降低射频电路串扰噪声的布线方法

研究并解决了无障碍多层无网格射频电路的布线问题,主要包括三个部分:设计规则、串扰噪声限制和布线方法.首先通过设计规则计算连线参数,运用RLc模型估算串扰噪声,然后,按照需要连接的实节点个数进行归类并提出相应的布线算法.实验结果表明,该布线方法可有效地降低射频电路的串扰噪声.     

Interaction bounds in multivariable control systems

Time-domain limitations due to right half-plane zeros and poles in linear multivariable control systems are studied. Lower bounds on the interaction are derived. They show not only how the location of zeros and poles are critical in multivariable systems, but also how the zero and pole directions influence the performance. The results are illustrated on the quadruple-tank process, which is a new multivariable laboratory process.     

一种新型特级防火卷帘的研究与开发——3J特级防火卷帘

介绍3J特级防火卷帘的各种重要功能特点,讨论其实用性与易用性以及推广该产品的必要性与可行性。     

Hardware and software architecture for power quality analysis

This paper presents a novel concept for power quality hardware and software architecture. Software tools related to detection, classification and characterization of power quality events can be integrated into a Distribution Control Center in which the interconnection between different subsystems is being carried out through the Internet allowing flexibility to the system. This system is implemented using wavelet analysis applied in all proposed algorithms. Different power quality events are taken as examples to illustrate the capabilities of the proposed method. The obtained results reveal that the proposed architecture is feasible to be implemented as an integral part of a control center system.The proposed system has the property of fast and accurate detection and classification of any power quality disturbance event and introduces a new PQ index determination that allows characterizing any type of disturbance including the non-periodic signals.     

Extensions of LDA by PCA mixture model and class-wise features

Linear discriminant analysis (LDA) is a data discrimination technique that seeks transformation to maximize the ratio of the between-class scatter and the within-class scatter. While it has been successfully applied to several applications, it has two limitations, both concerning the underfitting problem. First, it fails to discriminate data with complex distributions since all data in each class are assumed to be distributed in the Gaussian manner. Second, it can lose class-wise information, since it produces only one transformation over the entire range of classes. We propose three extensions of LDA to overcome the above problems. The first extension overcomes the first problem by modelling the within-class scatter using a PCA mixture model that can represent more complex distribution. The second extension overcomes the second problem by taking different transformation for each class in order to provide class-wise features. The third extension combines these two modifications by representing each class in terms of the PCA mixture model and taking different transformation for each mixture component. It is shown that all our proposed extensions of LDA outperform LDA concerning classification errors for synthetic data classification, hand-written digit recognition, and alphabet recognition.     

A tolerant approach to reconstruct topology from unorganized trimmed surfaces

Presented in this paper is a topology reconstruction algorithm from a set of unorganized trimmed surfaces. Error-prone small geometric elements are handled to give proper topological information. It gives complete topology to topologically complete models, and it is also tolerant to incomplete models. The proposed algorithm is vertex-based in that clues for topological information are searched from the set of vertices first, not from that of edges.     

Formation and Characterization of 1.5-Monolayer Self-Assembled InAs/GaAs Quantum Dots Using Postgrowth Annealing

In this paper, we report that low-density InAs/GaAs quantum dots (QDs) can be formed by postgrowth annealing the samples with 1.5-monolayer (ML) InAs coverage, which is thinner than the critical layer thickness for the Stranski-Krastanov growth. The annealing procedure was performed immediately after the deposition of the InAs layer. The effects of annealing time and annealing temperature on the dot density, dot size, and optical characteristics of the QDs were investigated. The optimum annealing conditions to obtain low-density QDs are longer than 60 s and higher than 500degC . Meanwhile, no luminescence can be observed for the wetting-layer, which may suggest that the postgrowth annealing will make the wetting layer thinner and thus reduce the effects of wetting layer on carrier relaxation and recombination. On the other hand, we observe that a decrease of the PL intensity at the annealing conditions of 60 s and 515degC , which is possibly due to the increasing surface dislocations resulted from the In adatom desorption at higher annealing temperature.