Exploiting Mn(III)/EDTA complex in a flow system with solenoid micro-pumps coupled to long pathlength spectrophotometry for fast manganese determination

The formation of the Mn(III)/EDTA complex in a flow system with solenoid micro-pumps was exploited for fast manganese determination in freshwater. Manganese(II) was oxidized in a solid-phase reactor containing lead dioxide immobilized on polyester. Long pathlength spectrophotometry was exploited to increase sensitivity, aiming to reach the threshold limit established by environmental legislation. A linear response was observed from 25 to 1500 mu g L(-1), with a detection limit of 6 mu g L(-1) (99.7% confidence level). Sample throughput and coefficient of variation were 36 samples/h and 2.6% (n = 10), respectively. EDTA consumption and waste generation were estimated as 500 mu g and 3 mL per determination, respectively. The amount of Pb in the residue corresponds to 250 mu g per determination and a solid-phase reactor could be used for up to 1600 determinations. Adsorption in active charcoal avoided interferences caused by organic matter and the developed procedure was successfully applied for determination of manganese in freshwater samples. Results were in agreement with those attained by GFAAS at the 95% confidence level. (C) 2010 Elsevier B.V. All rights reserved.

A multicommuted flow system with solenoid micro-pumps for paraquat determination in natural waters

A flow system designed with solenoid micro-pumps is proposed for the determination of paraquat in natural waters. The procedure involves the reaction of paraquat with dehydroascorbic acid followed by spectrophotometric measurements. The proposed procedure minimizes the main drawbacks related to the standard chromatographic procedure and to flow analysis and manual methods with spectrophotometric detection based on the reaction with sodium dithionite, i.e. high solvent consumption and waste generation and low sampling rate for chromatography and high instability of the reagent in the spectrophotometric procedures. A home-made 10-cm optical-path flow cell was employed for improving sensitivity and detection limit. Linear response was observed for paraquat concentrations in the range 0.10-5.0 mg L-1. The detection limit (99.7% confidence level), sampling rate and coefficient of variation (n = 10) were estimated as 22 mu g L-1, 63 measurements per hour and 1.0%, respectively. Results of determination of paraquat in natural water samples were in agreement with those achieved by the chromatographic reference procedure at the 95% confidence level. (c) 2008 Elsevier B.V. All rights reserved.

An algorithm for computerized automatic tuning of power system stabilizers

The main objective of this paper is to relieve the power system engineers from the burden of the complex and time-consuming process of power system stabilizer (PSS) tuning. To achieve this goal, the paper proposes an automatic process for computerized tuning of PSSs, which is based on an iterative process that uses a linear matrix inequality (LMI) solver to find the PSS parameters. It is shown in the paper that PSS tuning can be written as a search problem over a non-convex feasible set. The proposed algorithm solves this feasibility problem using an iterative LMI approach and a suitable initial condition, corresponding to a PSS designed for nominal operating conditions only (which is a quite simple task, since the required phase compensation is uniquely defined). Some knowledge about the PSS tuning is also incorporated in the algorithm through the specification of bounds defining the allowable PSS parameters. The application of the proposed algorithm to a benchmark test system and the nonlinear simulation of the resulting closed-loop models demonstrate the efficiency of this algorithm. (C) 2009 Elsevier Ltd. All rights reserved.

Automatic tuning method for the design of supplementary damping controllers for flexible alternating current transmission system devices

The design of supplementary damping controllers to mitigate the effects of electromechanical oscillations in power systems is a highly complex and time-consuming process, which requires a significant amount of knowledge from the part of the designer. In this study, the authors propose an automatic technique that takes the burden of tuning the controller parameters away from the power engineer and places it on the computer. Unlike other approaches that do the same based on robust control theories or evolutionary computing techniques, our proposed procedure uses an optimisation algorithm that works over a formulation of the classical tuning problem in terms of bilinear matrix inequalities. Using this formulation, it is possible to apply linear matrix inequality solvers to find a solution to the tuning problem via an iterative process, with the advantage that these solvers are widely available and have well-known convergence properties. The proposed algorithm is applied to tune the parameters of supplementary controllers for thyristor controlled series capacitors placed in the New England/New York benchmark test system, aiming at the improvement of the damping factor of inter-area modes, under several different operating conditions. The results of the linear analysis are validated by non-linear simulation and demonstrate the effectiveness of the proposed procedure.

A simple method for non-linear analysis of steel fiber reinforced concrete

This paper proposes a physical non-linear formulation to deal with steel fiber reinforced concrete by the finite element method. The proposed formulation allows the consideration of short or long fibers placed arbitrarily inside a continuum domain (matrix). The most important feature of the formulation is that no additional degree of freedom is introduced in the pre-existent finite element numerical system to consider any distribution or quantity of fiber inclusions. In other words, the size of the system of equations used to solve a non-reinforced medium is the same as the one used to solve the reinforced counterpart. Another important characteristic of the formulation is the reduced work required by the user to introduce reinforcements, avoiding ""rebar"" elements, node by node geometrical definitions or even complex mesh generation. Bounded connection between long fibers and continuum is considered, for short fibers a simplified approach is proposed to consider splitting. Non-associative plasticity is adopted for the continuum and one dimensional plasticity is adopted to model fibers. Examples are presented in order to show the capabilities of the formulation.

Characterization of micro-bubble size distribution and flow configuration in DAF contact zone by a non-intrusive image analysis system and tracer tests

This paper aims to investigate the influence of some dissolved air flotation (DAF) process variables (specifically: the hydraulic detention time in the contact zone and the supplied dissolved air concentration) and the pH values, as pretreatment chemical variables, on the micro-bubble size distribution (BSD) in a DAF contact zone. This work was carried out in a pilot plant where bubbles were measured by an appropriate non-intrusive image acquisition system. The results show that the obtained diameter ranges were in agreement with values reported in the literature (10-100mm), quite independently of the investigated conditions. The linear average diameter varied from 20 to 30mm, or equivalently, the Sauter (d(3,2)) diameter varied from 40 to 50mm. In all investigated conditions, D(50) was between 75% and 95%. The BSD might present different profile (with a bimodal curve trend), however, when analyzing the volumetric frequency distribution (in some cases with the appearance of peaks in diameters ranging from 90-100mm). Regarding volumetric frequency analysis, all the investigated parameters can modify the BSD in DAF contact zone after the release point, thus potentially causing changes in DAF kinetics. This finding prompts further research in order to verify the effect of these BSD changes on solid particle removal efficiency by DAF.

Treatment of linear alkylbenzene sulfonate in a horizontal anaerobic immobilized biomass reactor

Linear alkylbenzene sulfonate (LAS) is an anionic surfactant widely used to manufacture detergents and found in domestic and industrial wastewater. LAS removal was evaluated in a horizontal anaerobic immobilized biomass reactor. The system was filled with polyurethane foam and inoculated with sludge that was withdrawn from an up flow anaerobic sludge blanket reactor that is used to treat swine wastewater. The reactor was fed with easily degradable substrates and a solution of commercial LAS for 313 days. The hydraulic retention time applied was 12 h. The system was initially operated without detergent and resulted to 94% reduction of demand. The mass balance in the system indicated that the LAS removal efficiency was 45% after 180 days. From the 109th day to the 254th day, a removal efficiency of 32% was observed. The removal of LAS was approximately 40% when 1500 mg of LAS were applied in the absence of co-substrates suggesting that the LAS molecules were used selectively. Microscopic analyses of the biofilm revealed diverse microbial morphologies and denaturing gradient gel electrophoresis profiling showed variations in the total bacteria and sulfate-reducing bacteria populations. 16S rRNA sequencing and phylogenetic analyses demonstrated that members of the order Clostridiales were the major components of the bacterial community in the last step of the reactor operation. (c) 2009 Elsevier Ltd. All rights reserved.

Recursive linear estimation for general discrete-time descriptor systems

This paper considers the optimal linear estimates recursion problem for discrete-time linear systems in its more general formulation. The system is allowed to be in descriptor form, rectangular, time-variant, and with the dynamical and measurement noises correlated. We propose a new expression for the filter recursive equations which presents an interesting simple and symmetric structure. Convergence of the associated Riccati recursion and stability properties of the steady-state filter are provided. (C) 2010 Elsevier Ltd. All rights reserved.

Information Filtering and Array Algorithms for Discrete-Time Markovian Jump Linear Systems

This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.

On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

Discrete-time mean variance optimal control of linear systems with Markovian jumps and multiplicative noise

In this article, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under three kinds of performance criterions related to the final value of the expectation and variance of the output. In the first problem it is desired to minimise the final variance of the output subject to a restriction on its final expectation, in the second one it is desired to maximise the final expectation of the output subject to a restriction on its final variance, and in the third one it is considered a performance criterion composed by a linear combination of the final variance and expectation of the output of the system. We present explicit sufficient conditions for the existence of an optimal control strategy for these problems, generalising previous results in the literature. We conclude this article presenting a numerical example of an asset liabilities management model for pension funds with regime switching.

A calibration approach based on Takagi-Sugeno fuzzy inference system for digital electronic compasses

Recently, the development of industrial processes brought on the outbreak of technologically complex systems. This development generated the necessity of research relative to the mathematical techniques that have the capacity to deal with project complexities and validation. Fuzzy models have been receiving particular attention in the area of nonlinear systems identification and analysis due to it is capacity to approximate nonlinear behavior and deal with uncertainty. A fuzzy rule-based model suitable for the approximation of many systems and functions is the Takagi-Sugeno (TS) fuzzy model. IS fuzzy models are nonlinear systems described by a set of if then rules which gives local linear representations of an underlying system. Such models can approximate a wide class of nonlinear systems. In this paper a performance analysis of a system based on IS fuzzy inference system for the calibration of electronic compass devices is considered. The contribution of the evaluated IS fuzzy inference system is to reduce the error obtained in data acquisition from a digital electronic compass. For the reliable operation of the TS fuzzy inference system, adequate error measurements must be taken. The error noise must be filtered before the application of the IS fuzzy inference system. The proposed method demonstrated an effectiveness of 57% at reducing the total error based on considered tests. (C) 2011 Elsevier Ltd. All rights reserved.

Linear minimum mean square filter for discrete-time linear systems with Markov jumps and multiplicative noises

In this paper we obtain the linear minimum mean square estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline. (c) 2011 Elsevier Ltd. All rights reserved.

Flow rate sprinkler development for site-specific irrigation

Due to the rapid depletion of water resources, water must be used more efficiently in agriculture to maintain current levels of yield in irrigated areas. The efficiency of irrigation systems can be increased by adjusting the amount of water applied to specific conditions of soil and crop, which may vary in a field. Taking into account spatial and temporal variability, it is evident that an equipment capable of providing different irrigation levels is necessary to meet the water requirement of the soil. This work aims to develop and evaluate a flow rate sprinkler to be used in center pivots or linear moving irrigation systems, with potential for utilization in irrigation scheduling. A prototype was developed by duplicating its calibrations, and discharge coefficient adjustment was carried out in the laboratory. To predict the flow rate, a successful model that represented the operation of the flow rate sprinkler was established. The calibration of the flow rate sprinkler prototype showed satisfactory statistical and technical results. Automation of the prototype was achieved by driving a step motor using communication from the parallel port of a microcomputer, which was controlled by a software developed for this purpose. The results were satisfactory and technically feasible.