Robust tracking control design for uncertain robotic systems with persistent bounded disturbances

In this study, a robust nonlinear L_∞‐gain tracking control design for uncertain robotic systems is proposed under persistent bounded disturbances. The design objective is that the peak of the tracking error in time domain must be as small as possible under persistent bounded disturbances. Since the nonlinear L_∞ ‐gain optimal tracking control cannot be solved directly, the nonlinear L_∞ ‐gain optimal tracking problem is transformed into a nonlinear L_∞ ‐gain tracking problem by given a prescribed disturbance attenuation level for the L_∞ ‐gain tracking performance. To guarantee that the L_∞ ‐gain tracking performance can be achieved for the uncertain robotic systems, a sliding‐mode scheme is introduced to eliminate the effect of the parameter uncertainties. By virtue of the skew‐symmetric property of the robotic systems, sufficient conditions are developed for solving the robust L_∞ ‐gain tracking control problems in terms of an algebraic equation instead of a differential equation. The proposed method is simple and the algebraic equation can be solved analytically. Therefore, the proposed robust L_∞ ‐gain tracking control scheme is suitable for practical control design of uncertain robotic systems. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

A well-based reverse-phase protein array applicable to extracts from formalin-fixed paraffin-embedded tissue

Proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissue offers significant diagnostic utility but is complicated due to the high level of covalently crosslinked proteins arising from formalin fixation. To address these challenges, we developed a reliable protein extraction method for FFPE tissue, based on heat-induced antigen retrieval within a pressure cooker. The protein extraction yield from archival FFPE tissue section is approximately 90% of that recovered from frozen tissue. This method demonstrates preservation of immunoreactivity and recovery of full-length proteins by Western blotting. Additionally, we developed a well-based RP protein array platform utilizing an electrochemiluminescence detection system. Protein samples derived from FFPE tissue by means of laser capture dissection, with as few as 500 shots demonstrate measurable signal differences for different proteins. The lysates coated to the array plate, remain stable over 1?month at room temperature. Theses data suggest that this new protein-profiling platform coupled with the protein extraction method can be used for molecular profiling analysis in FFPE tissue, and contribute to the validation and development of biomarkers in clinical studies.     

Efficient Compositing Methods for the Sort-Last-Sparse Parallel Volume Rendering System on Distributed Memory Multicomputers

In the sort-last-sparse parallel volume rendering system on distributed memory multicomputers, one can achieve a very good performance improvement in the rendering phase by increasing the number of processors. This is because each processor can render images locally without communicating with other processors. However, in the compositing phase, a processor has to exchange local images with other processors. When the number of processors exceeds a threshold, the image compositing time becomes a bottleneck. In this paper, we propose three compositing methods to efficiently reduce the compositing time in parallel volume rendering. They are the binary-swap with bounding rectangle (BSBR) method, the binary-swap with run-length encoding and static load-balancing (BSLC) method, and the binary-swap with bounding rectangle and run-length encoding (BSBRC) method. The proposed methods were implemented on an SP2 parallel machine along with the binary-swap compositing method. The experimental results show that the BSBRC method has the best performance among these four methods.     

Transient temperature responses of hydronic radiant floor heating system by different pipe embedding depth and water supply condition

"Ondol" is a Korean unique heating system. It is a specific radiant floor heating system using combustion heat of briquette or timber in Korea. Such traditional "Ondol" is changed to radiant heating system with pipe-coil embedded in the floor or slab. This study has contributed to the understandings of the transient behaviours of Ondol-heated floor panels and enclosure exposed to this type of heating system. The result is that the water supply temperature had a large effect on the rate of increase in floor surface and room air temperature. But, in spite of a higher water supply temperature, the heat flow rate was not increased considerably. The shallow pipe embedding depths, of course, result in a low heat flow rate.     

Effects of user age and target-expansion methods on target-acquisition tasks using a mouse

Target expansion, i.e., the increase of target size according to cursor movement, can be a practical scheme to improve the usability of target-selection tasks using a mouse. This study examined the effects of different user age groups and target-expansion methods on target-acquisition tasks with grouped icons. Twenty-eight subjects performed acquisition tasks under eight experimental conditions: combinations of four expansion areas (no, one-icon, fish-eye, and group expansion) and two expansion techniques (occlusion and push). Older users took longer to acquire targets than younger users; however, they showed no significant difference in accuracy. Target expansion did not substantially improve performance speed compared to the static condition. However, the error rate was lowest when group area was expanded with the push technique, and both age groups were most satisfied with one-icon area expansion with the occlusion technique. We suggest alternative guidelines in designing target-expansion schemes.     

A novel frequency-offset monitoring technique for direct-detection DPSK systems

We propose and demonstrate a novel technique to monitor the frequency offset between the optical source and delay interferometer (DI) for direct-detection differential phase-shift-keying (DPSK) systems. In this scheme, a phase-modulated tone is applied to DPSK signals at the transmitter and then detected after being converted into an amplitude-modulated tone at the DI to be used for the monitoring signal. Our experimental demonstration shows that the monitoring range and sensitivity of the proposed scheme are measured to be /spl plusmn/2 GHz and /spl sim/10 MHz, respectively, which we believe are good enough to be used either to generate alarm signals for the frequency offset monitoring or to control the feedback loop of the DI.     

Comments on “Quadratic stabilization of continuous timesystems with state-delay and norm-bounded time-varyinguncertainties”

In the above mentioned paper by Mahmoud-Muthairi (ibid. vol.39 (1994)) a sufficient condition for memoryless stabilization of a class of uncertain linear systems with a variable-state delay and norm-bounded time-varying uncertainties is derived in terms of an algebraic Riccati equation. This Riccati equation depends on several free matrix variables, and a subsequent result in the paper, Theorem 2, states that failure or success of the stabilization algorithm is independent of the selection of these matrix variables. In this paper, we give a counterexample to this Theorem 2 as well as providing a fix     

Parallel finding all initial palindromes and periods of a string on reconfigurable meshes

Given a string of lengthn, this short paper first presents anO(1)-time parallel algorithm for finding all initial palindromes and periods of the string on ann×n reconfigurable mesh (RM). Then, under the same cost (= time × the number of processors =O(n ²)), we provide a partitionable strategy when the RM doesn’t offer sufficient processors; this overcomes the hardware limitation and is very suitable for VLSI implementation. Prof. Chung was supported in part by the National Science Council of R. O. C. under contracts NSC87-2213-E011-001 and NSC87-2213-E011-003.     

Application of multi-layer perceptron neural networks to vision problems

This paper discusses the application of a class of feed-forward Artificial Neural Networks (ANNs) known as Multi-Layer Perceptrons(MLPs) to two vision problems: recognition and pose estimation of 3D objects from a single 2D perspective view; and handwritten digit recognition. In both cases, a multi-MLP classification scheme is developed that combines the decisions of several classifiers. These classifiers operate on the same feature set for the 3D recognition problem whereas different feature types are used for the handwritten digit recognition. The backpropagationlearning rule is used to train the MLPs. Application of the MLP architecture to other vision problems is also briefly discussed.