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.     

Putting it all together – Formal verification of the VAMP

In the verified architecture microprocessor (VAMP) project we have designed, functionally verified, and synthesized a processor with full DLX instruction set, delayed branch, Tomasulo scheduler, maskable nested precise interrupts, pipelined fully IEEE compatible dual precision floating point unit with variable latency, and separate instruction and data caches. The verification has been carried out in the theorem proving system PVS. The processor has been implemented on a Xilinx FPGA. A shorter version of this article with the title “Instantiating uninterpreted functional units and memory system: functional verification of the VAMP” appeared in [8]. The work reported here was done while all the authors were with Saarland University.     

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.     

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.     

Profile-Based Linguistic Uniformity as a Generic Method for Comparing Language Varieties

In this text we present``profile-based linguistic uniformity', a methoddesigned to compare language varieties on thebasis of a wide range of potentiallyheterogeneous linguistic variables. In manyrespects a parallel can be drawn with currentmethods in dialectometry (for an overview, see,Nerbonne and Heeringa, 2001; Heeringa, Nerbonneand Kleiweg, 2002): in both casesdissimilarities between varieties on the basisof individual variables are summarized inglobal dissimilarities, and a series oflanguage varieties are subsequently clusteredor charted using multivariate techniques suchas cluster analysis or multidimensionalscaling. This global similarity between themethods makes it possible to compare them andto investigate the implications of notabledifferences. In this text we specifically focuson, and defend one characteristic of ourmethodology, its profile-based nature.     

A Simon Effect With Stationary Moving Stimuli.

To clarify whether motion information per se has a separable influence on action control, the authors investigated whether irrelevant direction of motion of stimuli whose overall position was constant over time would affect manual left-right responses (i.e., reveal a motion-based Simon effect). In Experiments 1 and 2, significant Simon effects were obtained for sine-wave gratings moving in a stationary Gaussian window. In Experiment 3, a direction-based Simon effect with random-dot patterns was replicated, except that the perceived direction of motion was based on the displacement of single elements. Experiments 4 and 5 studied motion-based Simon effects to point-light figures that walked in place--displays requiring high-level analysis of global shape and local motion. Motion-based Simon effects occurred when the displays could be interpreted as an upright human walker, showing that a high-level representation of motion direction mediated the effects. Thus, the present study establishes links between high-level motion perception and action. (PsycINFO Database Record (c) 2010 APA, all rights reserved)