Filters method in direct search optimization, new measures to admissibility

Constrained nonlinear optimization problems are usually solved using penalty or barrier methods combined with unconstrained optimization methods. Another alternative used to solve constrained nonlinear optimization problems is the lters method. Filters method, introduced by Fletcher and Ley er in 2002, have been widely used in several areas of constrained nonlinear optimization. These methods treat optimization problem as bi-objective attempts to minimize the objective function and a continuous function that aggregates the constraint violation functions. Audet and Dennis have presented the rst lters method for derivative-free nonlinear programming, based on pattern search methods. Motivated by this work we have de- veloped a new direct search method, based on simplex methods, for general constrained optimization, that combines the features of the simplex method and lters method. This work presents a new variant of these methods which combines the lters method with other direct search methods and are proposed some alternatives to aggregate the constraint violation functions.

Experimental evaluation of position control methods for hydraulic systems

Presents a unified and systematic assessment of ten position control strategies for a hydraulic servo system with single-ended cylinder driven by a proportional directional control valve. We aim at identifying those methods that achieve better tracking, have a low sensitivity to system uncertainties, and offer a good balance between development effort and end results. A formal approach for solving this problem relies on several practical metrics, which is introduced herein. Their choice is important, as the comparison results between controllers can vary significantly, depending on the selected criterion. Apart from the quantitative assessment, we also raise aspects which are difficult to quantify, but which must stay in attention when considering the position control problem for this class of hydraulic servo systems.

Driving speed is altered by monocular Neutral Density filters : the Enright phenomenon

Introduction: An observer, looking sideways from a moving vehicle, while wearing a neutral density filter over one eye, can have a distorted perception of speed, known as the Enright phenomenon. The purpose of this study was to determine how the Enright phenomenon influences driving behaviour. Methods: A geometric model of the Enright phenomenon was developed. Ten young, visually normal, participants (mean age = 25.4 years) were tested on a straight section of a closed driving circuit and instructed to look out of the right side of the vehicle and drive at either 40 Km/h or 60 Km/h under the following binocular viewing conditions: with a 0.9 ND filter over the left eye (leading eye); 0.9 ND filter over the right eye (trailing eye); 0.9 ND filters over both eyes, and with no filters over either eye. The order of filter conditions was randomised and the speed driven recorded for each condition. Results: Speed judgments did not differ significantly between the two baseline conditions (no filters and both eyes filtered) for either speed tested. For the baseline conditions, when subjects were asked to drive at 60 Km/h they matched this speed well (61 ± 10.2 Km/h) but drove significantly faster than requested (51.6 ± 9.4 Km/h) when asked to drive at 40 Km/h. Subjects significantly exceeded baseline speeds by 8.7± 5.0 Km/h, when the trailing eye was filtered and travelled slower than baseline speeds by 3.7± 4.6 Km/h when the leading eye was filtered. Conclusions: This is the first quantitative study demonstrating how the Enright effect can influence perceptions of driving speed, and demonstrates that monocular filtering of an eye can significantly impact driving speeds, albeit to a lesser extent than predicted by geometric models of the phenomenon.

Extended Kalman filters using explicit and derivative-free local linearizations

We propose three variants of the extended Kalman filter (EKF) especially suited for parameter estimations in mechanical oscillators under Gaussian white noises. These filters are based on three versions of explicit and derivative-free local linearizations (DLL) of the non-linear drift terms in the governing stochastic differential equations (SDE-s). Besides a basic linearization of the non-linear drift functions via one-term replacements, linearizations using replacements through explicit Euler and Newmark expansions are also attempted in order to ensure higher closeness of true solutions with the linearized ones. Thus, unlike the conventional EKF, the proposed filters do not need computing derivatives (tangent matrices) at any stage. The measurements are synthetically generated by corrupting with noise the numerical solutions of the SDE-s through implicit versions of these linearizations. In order to demonstrate the effectiveness and accuracy of the proposed methods vis-à-vis the conventional EKF, numerical illustrations are provided for a few single degree-of-freedom (DOF) oscillators and a three-DOF shear frame with constant parameters.

Use of narrow-pore filters in He II transfer devices - new results

With the aim of finding simple methods for the fabrication of He II refilling devices, He II flow has been studied through filters made from various fine powders (oxides and metals, grain sizes in the range 0.05–2 μm) by compacting them under pressure. The results obtained for the different states of He II flow, especially in the “breakthrough” and “easy flow” range, are explained by the fountain effect, He II hydrodynamics and the choking effect. According to the results, pressedpowder filters can be classified into three groups with different flow characteristics, of which the “good transfer filters” with a behaviour neatly described by simple theory are suitable for use in He II refilling devices.

Commercial application of polychaete sand filters for wastewater remediation and broodstock feeds

Summary Prototype sand-worm filtration beds were constructed at two prawn farms and one fish farm to assess and demonstrate their polychaete (marine worm) production and wastewater remediation capacities at semi-commercial scale. Wastewater treatment properties were monitored and worms produced were assessed and either sold for bait or used by the farms’ hatcheries as broodstock (prawn or fish breeder) feed. More than 34 megalitres of prawn- and fish-pond water was beneficially treated in the 116-319-d trial. The design of the polychaete-assisted sand filters (PASFs) constructed at each farm affected their water handling rates, which on average ranged from 315 to 1000 L m-2 d-1 at the three farms. A low profile design incorporating shallow bunded ponds made from polyethylene liner and timber stakes provided the easiest method of construction. This simple design applied at broad scale facilitated the highest quantities of treated water and the greatest worm production. Designs with higher sides increased the head pressure above the sand bed surface, thus increasing the amount of water that could be treated each day. Most water qualities were affected in a similar way to that demonstrated in the previous tank trials: dissolved oxygen, pH, total suspended solids and chlorophyll a levels were all consistently significantly lowered as pond water percolated through the sand bed, and dissolved forms of nitrogen and phosphorus were marginally increased on several occasions. However, unlike the previous smaller-scale tank trials, total nitrogen (TN) and total phosphorus (TP) levels were both significantly lowered by these larger-scale PASFs. The reasons for this are still unclear and require further research. Maximum TN and TP removals detected in the trial were 48.8% and 67.5%, respectively, and average removals (in unfed beds) at the three farms ranged from 20.0 to 27.7% for TN and from 22.8 to 40.8% for TP. Collectively, these results demonstrate the best suspended solids, chlorophyll and macronutrient removal capacities so far reported for any mariculture wastewater treatment methodology to date. Supplemental feeding of PASFs with fish meal was also investigated at one farm as a potential means of increasing their polychaete biomass production. Whilst fed beds produced higher biomass (152 ± 35 g m-2) compared with unfed beds (89 ± 17 g m-2) after 3.7 months of operation, the low number of replicates (2) prevented statistically significant differences from being demonstrated for either growth or survival. At harvest several months later, worm biomass production was estimated to be similar to, or in slight excess of, previously reported production levels (300-400 g m-2). Several qualities of filtered water appear to have been affected by supplemental feeding: it appeared to marginally lower dissolved oxygen and pH levels, and increased the TN and TP levels though not so much to eliminate significant beneficial water treatment effects. Periodic sampling during an artificial-tide demonstrated the tendency for treated-water quality changes during the first hour of filtration. Total nitrogen and ammonia peaked early in the tidal flow and then fell to more stable levels for the remainder of the filtration period. Other dissolved nutrients also showed signs of this sand-bed-flushing pattern, and dissolved oxygen tended to climb during the first hour and become more stable thereafter. These patterns suggest that the routine sampling of treated water undertaken at mid-inflow during the majority of the wider study would likely have overestimated the levels of TN and dissolved nutrients discharged from the beds, and hence underestimated the PASFs treatment efficacies in this regard. Analyses of polychaete biomass collected from each bed in the study revealed that the worms were free from contamination with the main prawn viruses that would create concerns for their feeding to commercial prawn broodstock in Australia. Their documented proximal and nutritional contents also provide a guide for hatchery operators when using live or frozen stock. Their dry matter content ranged from 18.3 to 22.3%, ash ranged from 10.2 to 14.0%, gross energy from 20.2 to 21.5 MJ kg-1, and fat from 5.0 to 9.2%. Their cholesterol levels ranged from 0.86 to 1.03% of dry matter, whilst total phospholipids range from 0.41 to 0.72%. Thirty-one different fatty acids were present at detectable (≥0.005% of dry matter) levels in the sampled worm biomass. Palmitic acid was by far the most prevalent fatty acid detected (1.21 ± 0.18%), followed by eicosapentaenoic (EPA) (0.48 ± 0.03%), stearic (0.46 ± 0.04%), vaccenic (0.38 ± 0.05%), adrenic (0.35 ± 0.02%), docosadienoic (0.28 ± 0.02%), arachidonic (AA) (0.22 ± 0.01%), palmitoleic (0.20 ± 0.04%) and 23 other fatty acids with average contents of less than 0.2% of dry matter. Supplemental feeding with fish meal at one farm appeared to increase the docosahexaenoic acid (DHA) content of the worms considerably, and modify the average AA : EPA : DHA from 1.0 : 2.7 : 0.3 to 1.0 : 2.0 : 1.1. Consistent with previous results, the three most heavily represented amino acids in the dry matter of sampled worms were glutamic acid (8.5 ± 0.2%), aspartic acid (5.5 ± 0.1%) and glycine (4.9 ± 0.5%). These biomass content results suggest that worms produced in PASF systems are well suited to feeding to prawn and fish broodstock, and provide further strong evidence of the potential to modify their contents for specific nutritional uses. The falling wild-fishery production of marine bloodworms in Queensland is typical of diminishing polychaete resources world-wide and demonstrates the need to develop sustainable production methods here and overseas. PASF systems offer the dual benefits of wastewater treatment for environmental management and increased productivity through a valuable secondary crop grown exclusively on waste nutrients.

Novel window functions for digital filters

Window technique is one of the simplest methods to design Finite Impulse Response (FIR) filters. It uses special functions to truncate an infinite sequence to a finite one. In this paper, we propose window techniques based on integer sequences. The striking feature of the proposed work is that it overcomes all the problems posed by floating point numbers and inaccuracy, as the sequences are made of only integers. Some of these integer window sequences, yield sharp transition, while some of them result in zero ripple in passband and stopband.

Data rectification and detection of trend shifts in jet engine path measurements using median filters and fuzzy logic

Filtering methods are explored for removing noise from data while preserving sharp edges that many indicate a trend shift in gas turbine measurements. Linear filters are found to be have problems with removing noise while preserving features in the signal. The nonlinear hybrid median filter is found to accurately reproduce the root signal from noisy data. Simulated faulty data and fault-free gas path measurement data are passed through median filters and health residuals for the data set are created. The health residual is a scalar norm of the gas path measurement deltas and is used to partition the faulty engine from the healthy engine using fuzzy sets. The fuzzy detection system is developed and tested with noisy data and with filtered data. It is found from tests with simulated fault-free and faulty data that fuzzy trend shift detection based on filtered data is very accurate with no false alarms and negligible missed alarms.

Analysis and design of split-capacitor resistive-inductive passive damping for LCL filters in grid-connected inverters

Grid-connected inverters require a third-order LCL filter to meet standards such as the IEEE Std. 519-1992 while being compact and cost-effective. LCL filter introduces resonance, which needs to be damped through active or passive methods. Passive damping schemes have less control complexity and are more reliable. This study explores the split-capacitor resistive-inductive (SC-RL) passive damping scheme. The SC-RL damped LCL filter is modelled using state space approach. Using this model, the power loss and damping are analysed. Based on the analysis, the SC-RL scheme is shown to have lower losses than other simpler passive damping methods. This makes the SC-RL scheme suitable for high power applications. A method for component selection that minimises the power loss in the damping resistors while keeping the system well damped is proposed. The design selection takes into account the influence of switching frequency, resonance frequency and the choice of inductance and capacitance values of the filter on the damping component selection. The use of normalised parameters makes it suitable for a wide range of design applications. Analytical results show the losses and quality factor to be in the range of 0.05-0.1% and 2.0-2.5, respectively, which are validated experimentally.

Iterated gain-based stochastic filters for dynamic system identification

We propose a novel form of nonlinear stochastic filtering based on an iterative evaluation of a Kalman-like gain matrix computed within a Monte Carlo scheme as suggested by the form of the parent equation of nonlinear filtering (Kushner-Stratonovich equation) and retains the simplicity of implementation of an ensemble Kalman filter (EnKF). The numerical results, presently obtained via EnKF-like simulations with or without a reduced-rank unscented transformation, clearly indicate remarkably superior filter convergence and accuracy vis-a-vis most available filtering schemes and eminent applicability of the methods to higher dimensional dynamic system identification problems of engineering interest. (C) 2013 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

An overview of sequential Monte Carlo methods for parameter estimation in general state-space models

Nonlinear non-Gaussian state-space models arise in numerous applications in control and signal processing. Sequential Monte Carlo (SMC) methods, also known as Particle Filters, are numerical techniques based on Importance Sampling for solving the optimal state estimation problem. The task of calibrating the state-space model is an important problem frequently faced by practitioners and the observed data may be used to estimate the parameters of the model. The aim of this paper is to present a comprehensive overview of SMC methods that have been proposed for this task accompanied with a discussion of their advantages and limitations.

Accelerogram processing using reliability bounds and optimal correction methods

This study addresses the problem of obtaining reliable velocities and displacements from accelerograms, a concern which often arises in earthquake engineering. A closed-form acceleration expression with random parameters is developed to test any strong-motion accelerogram processing method. Integration of this analytical time history yields the exact velocities, displacements and Fourier spectra. Noise and truncation can also be added. A two-step testing procedure is proposed and the original Volume II routine is used as an illustration. The main sources of error are identified and discussed. Although these errors may be reduced, it is impossible to extract the true time histories from an analog or digital accelerogram because of the uncertain noise level and missing data. Based on these uncertainties, a probabilistic approach is proposed as a new accelerogram processing method. A most probable record is presented as well as a reliability interval which reflects the level of error-uncertainty introduced by the recording and digitization process. The data is processed in the frequency domain, under assumptions governing either the initial value or the temporal mean of the time histories. This new processing approach is tested on synthetic records. It induces little error and the digitization noise is adequately bounded. Filtering is intended to be kept to a minimum and two optimal error-reduction methods are proposed. The "noise filters" reduce the noise level at each harmonic of the spectrum as a function of the signal-to-noise ratio. However, the correction at low frequencies is not sufficient to significantly reduce the drifts in the integrated time histories. The "spectral substitution method" uses optimization techniques to fit spectral models of near-field, far-field or structural motions to the amplitude spectrum of the measured data. The extremes of the spectrum of the recorded data where noise and error prevail are then partly altered, but not removed, and statistical criteria provide the choice of the appropriate cutoff frequencies. This correction method has been applied to existing strong-motion far-field, near-field and structural data with promising results. Since this correction method maintains the whole frequency range of the record, it should prove to be very useful in studying the long-period dynamics of local geology and structures.