Approaches to extended non-quadratic stability and stabilization conditions for discrete-time Takagi–Sugeno fuzzy systems

This paper provides simple and effective linear matrix inequality (LMI) characterizations for the stability and stabilization conditions of discrete-time Takagi–Sugeno (T–S) fuzzy systems. To do this, more general classes of non-parallel distributed compensation (non-PDC) control laws and non-quadratic Lyapunov functions are presented. Unlike the conventional non-quadratic approaches using only current-time normalized fuzzy weighting functions, we consider not only the current-time fuzzy weighting functions but also the l-step-past (l?0) and one-step-ahead ones when constructing the control laws and Lyapunov functions. Consequently, by introducing additional decision variables, it can be shown that the proposed conditions include the existing ones found in the literature as particular cases. Examples are given to demonstrate the effectiveness of the approaches.     

Visual enhancement of old documents with hyperspectral imaging

Hyperspectral imaging (HSI) of historical documents is becoming more common at national libraries and archives. HSI is useful for many tasks related to document conservation and management as it provides detailed quantitative measurements of the spectral reflectance of the document that is not limited to the visible spectrum. In this paper, we focus on how to use the invisible spectra, most notably near-infrared (NIR) bands, to assist in visually enhancing old documents. Specifically, we demonstrate how to use the invisible bands to improve the visual quality of text-based documents corrupted with undesired artifacts such as ink-bleed, ink-corrosion, and foxing. For documents of line drawings that suffer from low contrast, we use details found in the invisible bands to enhance legibility. The key components of our framework involve detecting regions in the document that can be enhanced by the NIR spectra, compositing the enhanced gradient map using the NIR bands, and reconstructing the final image from the composited gradients. This work is part of a collaborative effort with the Nationaal Archief of the Netherlands (NAN) and Art Innovation, a manufacturer of hyperspectral imaging hardware designed specially for historical documents. Our approach is evaluated on historical documents from NAN that exhibit degradations common to documents found in most archives and libraries.     

Analysis of zero-inflated clustered count data: A marginalized model approach

Min and Agresti (2005) proposed random effect hurdle models for zero-inflated clustered count data with two-part random effects for a binary component and a truncated count component. In this paper, we propose new marginalized models for zero-inflated clustered count data using random effects. The marginalized models are similar to Dobbie and Welsh’s (2001) model in which generalized estimating equations were exploited to find estimates. However, our proposed models are based on a likelihood-based approach. A Quasi-Newton algorithm is developed for estimation. We use these methods to carefully analyze two real datasets.     

A sales agent for part manufacturers: VMSA

The sales activity of most parts manufacturing companies is based on orders of buyers. The process of promotion, receipt and selection of orders of the parts manufacturers is closely coupled with the load status of the production lines. On deciding whether to accept an order or not, as well as negotiating with buyers, sales persons need information such as load and schedule of production lines, and manufacturability of the order. Manufacturability analysis, process planning, and scheduling are therefore key features in developing an agent of sales activity for the parts manufacturing business. In this paper, an intelligent agent, a virtual manufacturing-based sales agent (VMSA) with multi-agent architecture is proposed to support the sales activity for the parts manufacturers in the Internet environment. A VMSA has an integrated architecture of agent and virtual manufacturing. The prototype of VMSA has been developed for a machine parts manufacturing company that has lathe machines, drilling machines, cutting machines, and milling machines.     

Interactive classification for pre-integrated volume rendering of high-precision volume data

The pre-integrated volume rendering technique is widely used for creating high quality images. It produces good images even though the transfer function is nonlinear. Because the size of the pre-integration lookup table is proportional to the square of data precision, the required storage and computation load steeply increase for rendering of high-precision volume data. In this paper, we propose a method that approximates the pre-integration function proportional to the data precision. Using the arithmetic mean instead of the geometric mean and storing opacity instead of extinction density, this technique reduces the size and the update time of the pre-integration lookup table so that it classifies high-precision volume data interactively. We demonstrate performance gains for typical renderings of volume datasets.     

Suboptimal filter for continuous‐time linear systems with unknown parameters

The filtering problem for continuous‐time linear systems with unknown parameters is considered. A new suboptimal filter is herein proposed. It is based on the optimal mean‐square linear combination of the local Kalman filters. In contrast to the optimal weights, the suboptimal weights do not depend on current observations; thus, the proposed filter can easily be implemented in real‐time. Examples demonstrate high accuracy and efficiency of the suboptimal filter. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Dynamic planning model for determining cutting parameters using neural networks in feature-based process planning

Although feature-based computer-aided process planning plays a vital role in automating and integrating design and manufacturing for efficient production, its off-line properties prohibit the shop floor controllers from rapidly coping with unexpected production errors. The objective of the paper is to suggest a neural network-based dynamic planning model, by which the shop floor controllers determine cutting parameters in real-time based on shop floor status. At off-line is the dynamic planning model constructed as a neural network form, and then embedded into each removal feature. The dynamic planning model will be executed by the shop floor controllers to determine the cutting parameters. A prototype system is constructed to validate whether the dynamic planning model is capable of determining dynamically and efficiently the cutting parameters for a particular set of shop operating factors. Owing to the dynamic planning model, the shop floor controller will increase flexibility and robustness by rapidly and adaptively determining the cutting parameters in unexpected errors occurring.     

Capturing and reusing knowledge in engineering change management: A case of automobile development

The development of complex products, such as automobiles, involves engineering changes that frequently require redesigning or altering the products. Although it has been found that efficient management of knowledge and collaboration in engineering changes is crucial for the success of new product development, extant systems for engineering changes focus mainly on storing documents related to the engineering changes or simply automating the approval processes, while the knowledge that is generated from collaboration and decision-making processes may not be captured and managed easily. This consequently limits the use of the systems by the participants in engineering change processes. This paper describes a model for knowledge management and collaboration in engineering change processes, and based on the model, builds a prototype system that demonstrates the model’s strengths. We studied a major Korean automobile company to analyze the automobile industry’s unique requirements regarding engineering changes. We also developed domain ontologies from the case to facilitate knowledge sharing in the design process. For achieving efficient retrieval and reuse of past engineering changes, we used a case-based reasoning (CBR) with a concept-based similarity measure.

Comments on “A new robust control for a class of uncertaindiscrete-time systems”

A completed proof for a theorem on the robust controller design proposed in Wang and Ghosh (ibid. vol.43 (1997)) is presented in this paper     

Correlation between acidic properties of nickel sulfate supported on TiO2-ZrO2 and catalytic activity for ethylene dimerization

A series of catalysts, NiSO₄/TiO₂-ZrO₂, for ethylene dimerization was prepared by the impregnation method using an aqueous solution of nickel sulfate. For NiSO₄/TiO₂ -ZrO₂ sample, no diffraction line of nickel sulfate was observed up to 30 wt%, indicating good dispersion of nickel sulfate on the surface of TiO₂-ZrO₂. The addition of nickel sulfate to TiO₂-ZrO₂ shifted the phase transition of TiZrO₄ from amorphous to orthorhombic to a higher temperature because of the interaction between nickel sulfate and TiO₂-ZrO₂. The number of acid sites of NiSO₄/TiO₂-ZrO₂ increased in proportion to the nickel sulfate content up to 20 wt% of NiSO₄. Nickel sulfate supported on TiO₂-ZrO₂ was found to be very active even at room temperature, giving a maximum in both activity and acidity when the catalyst containing 20% NiSO₄ was calcined and evacuated at 500°C The asymmetric stretching frequency of the S=O bonds for NiSO₄/TiO₂-ZrO₂ samples was related to the acidic properties and catalytic activity. That is, the higher the frequency, the higher both the number of acid sites and the catalytic activity for ethylene dimerization.