Accurate image capturing control of bottle caps based on iterative learning control and Kalman filtering

This paper investigates camera control for capturing bottle cap target images in the fault-detection system of an industrial production line. The main purpose is to identify the targeted bottle caps accurately in real time from the images. This is achieved by combining iterative learning control and Kalman filtering to reduce the effect of various disturbances introduced into the detection system. A mathematical model, together with a physical simulation platform is established based on the actual production requirements, and the convergence properties of the model are analyzed. It is shown that the proposed method enables accurate real-time control of the camera, and further, the gain range of the learning rule is also obtained. The numerical simulation and experimental results confirm that the proposed method can not only reduce the effect of repeatable disturbances but also non-repeatable ones.

Plant-wide predictive control for a thermal power plant based on a physical plant model

A constrained non-linear, physical model-based, predictive control (NPMPC) strategy is developed for improved plant-wide control of a thermal power plant. The strategy makes use of successive linearisation and recursive state estimation using extended Kalman filtering to obtain a linear state-space model. The linear model and a quadratic programming routine are used to design a constrained long-range predictive controller One special feature is the careful selection of a specific set of plant model parameters for online estimation, to account for time-varying system characteristics resulting from major system disturbances and ageing. These parameters act as nonstationary stochastic states and help to provide sufficient degrees-of-freedom to obtain unbiased estimates of controlled outputs. A 14th order non-linear plant model, simulating the dominant characteristics of a 200 MW oil-fired pou er plant has been used to test the NPMPC algorithm. The control strategy gives impressive simulation results, during large system disturbances and extremely high rate of load changes, right across the operating range. These results compare favourably to those obtained with the state-space GPC method designed under similar conditions.

Target Detection and Tracking With Heterogeneous Sensors

We present a multimodal detection and tracking algorithm for sensors composed of a camera mounted between two microphones. Target localization is performed on color-based change detection in the video modality and on time difference of arrival (TDOA) estimation between the two microphones in the audio modality. The TDOA is computed by multiband generalized cross correlation (GCC) analysis. The estimated directions of arrival are then postprocessed using a Riccati Kalman filter. The visual and audio estimates are finally integrated, at the likelihood level, into a particle filter (PF) that uses a zero-order motion model, and a weighted probabilistic data association (WPDA) scheme. We demonstrate that the Kalman filtering (KF) improves the accuracy of the audio source localization and that the WPDA helps to enhance the tracking performance of sensor fusion in reverberant scenarios. The combination of multiband GCC, KF, and WPDA within the particle filtering framework improves the performance of the algorithm in noisy scenarios. We also show how the proposed audiovisual tracker summarizes the observed scene by generating metadata that can be transmitted to other network nodes instead of transmitting the raw images and can be used for very low bit rate communication. Moreover, the generated metadata can also be used to detect and monitor events of interest.

High contrast plasma mirror: spatial filtering and second harmonic generation at 10(19)Wcm(-2)

Recently, the use of plasma optics to improve temporal pulse contrast has had a remarkable impact on the field of high- power laser-solid density interaction physics. Opening an avenue to previously unachievable plasma density gradients in the high intensity focus, this advance has enabled researchers to investigate new regimes of harmonic generation and ion acceleration. Until now, however, plasma optics for fundamental laser reflection have been used in the sub-relativistic intensity regime (10(15) - 10(16)Wcm(-2)) showing high reflectivity (similar to 70%) and good focusability. Therefore, the question remains as to whether plasma optics can be used for such applications in the relativistic intensity regime (> 10(18)Wcm(-2)). Previous studies of plasma mirrors (PMs) indicate that, for 40 fs laser pulses, the reflectivity fluctuates by an order of magnitude and that focusability of the beam is lost as the intensity is increased above 5 x 10(16)Wcm(-2). However, these experiments were performed using laser pulses with a contrast ratio of similar to 10(7) to generate the reflecting surface. Here, we present results for PM operation using high contrast laser pulses resulting in a new regime of operation - the high contrast plasma mirror (HCPM). In this regime, pulses with contrast ratio > 10(10) are used to form the PM surface at > 10(19)Wcm(-2), displaying excellent spatial filtering, reflected near- field beam profile of the fundamental beam and reflectivities of 60 +/- 5%. Efficient second harmonic generation is also observed with exceptional beam quality suggesting that this may be a route to achieving the highest focusable harmonic intensities. Plasma optics therefore offer the opportunity to manipulate ultra-intense laser beams both spatially and temporally. They also allow for ultrafast frequency up-shifting without detrimental effects due to group velocity dispersion (GVD) or reduced focusability which frequently occur when nonlinear crystals are used for frequency conversion.

Systolic building block for high performance recursive filtering

A novel bit level systolic array is presented that can be used as a building block in the construction of recursive digital filters. The circuit accepts bit-parallel input data, is pipelined at the bit level, and exhibits a very high throughput rate. The most important feature of the circuit is that it allows recursive operations to be implemented directly without incurring the large m cycle latency (where m is approximately the word length) normally associated with such systems. The use of this circuit in the construction of both first- and second-order IIR (infinite-impulse-response) filters is described.

Bit-Level systolic architectures for high performance IIR filtering

Several novel systolic architectures for implementing densely pipelined bit parallel IIR filter sections are presented. The fundamental problem of latency in the feedback loop is overcome by employing redundant arithmetic in combination with bit-level feedback, allowing a basic first-order section to achieve a wordlength-independent latency of only two clock cycles. This is extended to produce a building block from which higher order sections can be constructed. The architecture is then refined by combining the use of both conventional and redundant arithmetic, resulting in two new structures offering substantial hardware savings over the original design. In contrast to alternative techniques, bit-level pipelinability is achieved with no net cost in hardware. © 1989 Kluwer Academic Publishers.

Bit-level systolic arrays for IIR filtering.

A novel bit-level systolic array architecture for implementing IIR (infinite-impulse response) filter sections is presented. A first-order section achieves a latency of only two clock cycles by using a radix-2 redundant number representation, performing the recursive computation most significant digit first, and feeding back each digit of the result as soon as it is available. The design is extended to produce a building block from which second- and higher-order sections can be connected.

Ensuring the statistical soundness of competitive gene set approaches: gene filtering and genome-scale coverage are essential

In this article, we focus on the analysis of competitive gene set methods for detecting the statistical significance of pathways from gene expression data. Our main result is to demonstrate that some of the most frequently used gene set methods, GSEA, GSEArot and GAGE, are severely influenced by the filtering of the data in a way that such an analysis is no longer reconcilable with the principles of statistical inference, rendering the obtained results in the worst case inexpressive. A possible consequence of this is that these methods can increase their power by the addition of unrelated data and noise. Our results are obtained within a bootstrapping framework that allows a rigorous assessment of the robustness of results and enables power estimates. Our results indicate that when using competitive gene set methods, it is imperative to apply a stringent gene filtering criterion. However, even when genes are filtered appropriately, for gene expression data from chips that do not provide a genome-scale coverage of the expression values of all mRNAs, this is not enough for GSEA, GSEArot and GAGE to ensure the statistical soundness of the applied procedure. For this reason, for biomedical and clinical studies, we strongly advice not to use GSEA, GSEArot and GAGE for such data sets.

Dysfunctional filtering blebs

Guarded filtration surgery is commonly used to control the intraocular pressure (IOP) in glaucomatous patients. Filtration surgery lowers the IOP by creating a fistula between the inner compartments of the eye and the subconjunctival space (i.e., filtering bleb). There are several options to improve the function of filtering blebs and to prevent their failure. However, improvement of IOP control after guarded filtration procedures is associated with a higher frequency of bleb-related complications. Early (e.g., bleb leak, excessive filtration, flat anterior chamber, filtration failure) and late (e.g., bleb leak, excessive filtration and hypotony, symptomatic blebs, bleb encapsulation, filtration failure, bleb infection) complications associated with filtering procedures should be managed adequately to prevent further problems. Techniques to improve the function of filtering blebs and to treat postoperative complications have progressed over the past decade.

Frequency Filtering of Torsional Alfvén Waves by Chromospheric Magnetic Field

In this Letter, we demonstrate how the observation of broadband frequency propagating torsional Alfvén waves in chromospheric magnetic flux tubes can provide valuable insight into their magnetic field structure. By implementing a full nonlinear three-dimensional magnetohydrodynamic numerical simulation with a realistic vortex driver, we demonstrate how the plasma structure of chromospheric magnetic flux tubes can act as a spatially dependent frequency filter for torsional Alfvén waves. Importantly, for solar magnetoseismology applications, this frequency filtering is found to be strongly dependent on magnetic field structure. With reference to an observational case study of propagating torsional Alfvén waves using spectroscopic data from the Swedish Solar Telescope, we demonstrate how the observed two-dimensional spatial distribution of maximum power Fourier frequency shows a strong correlation with our forward model. This opens the possibility of beginning an era of chromospheric magnetoseismology, to complement the more traditional methods of mapping the magnetic field structure of the solar chromosphere.

Design methodology for low power and arametric robustness through output-quality modulation:Application to color-interpolation filtering

Power dissipation and robustness to process variation have conflicting design requirements. Scaling of voltage is associated with larger variations, while Vdd upscaling or transistor upsizing for parametric-delay variation tolerance can be detrimental for power dissipation. However, for a class of signal-processing systems, effective tradeoff can be achieved between Vdd scaling, variation tolerance, and output quality. In this paper, we develop a novel low-power variation-tolerant algorithm/architecture for color interpolation that allows a graceful degradation in the peak-signal-to-noise ratio (PSNR) under aggressive voltage scaling as well as extreme process variations. This feature is achieved by exploiting the fact that all computations used in interpolating the pixel values do not equally contribute to PSNR improvement. In the presence of Vdd scaling and process variations, the architecture ensures that only the less important computations are affected by delay failures. We also propose a different sliding-window size than the conventional one to improve interpolation performance by a factor of two with negligible overhead. Simulation results show that, even at a scaled voltage of 77% of nominal value, our design provides reasonable image PSNR with 40% power savings. © 2006 IEEE.