A barrier method for constrained nonlinear optimization using a modified Hopfield network

The ability of neural networks to realize some complex nonlinear function makes them attractive for system identification. This paper describes a novel barrier method using artificial neural networks to solve robust parameter estimation problems for nonlinear model with unknown-but-bounded errors and uncertainties. This problem can be represented by a typical constrained optimization problem. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach.

Alternative continuation method for loading margin improvement and transmission losses reduction

This paper presents an alternative methodology for loading margin improvement and total real power losses reduction by using a continuation method. In order to attain this goal, a parameterizing equation based on the total real power losses and the equations of the reactive power at the slack and generation buses are added to the conventional power flow equations. The voltages at these buses are considered as control variables and a new parameter is chosen to reduce the real power losses in the transmission lines. The results show that this procedure leads to maximum loading point increase and consequently, in static voltage stability margin improvement. Besides, this procedure also takes to a reduction in the operational costs and, simultaneously, to voltage profile improvement. Another important result of this methodology is that the resulting operating points are close to that provided by an optimal power flow program. © 2004 IEEE.

Enhanced multi-wavelength holographic profilometry by laser mode selection

The application of multi-wavelength holography for surface shape measurement is presented. In our holographic setup a Bi12TiO 20 (BTO) photorefractive crystal was the holographic recording medium and a multimode diode laser emitting in the red region was the light source in a two-wave mixing scheme. The holographic imaging with multimode lasers results in multiple holograms in the BTO. By employing such lasers the resulting holographic image appears covered of interference fringes corresponding to the object relief and the interferogram spatial frequency is proportional to the diode laser free spectral range (FSR). We used a Fabry-Perot étalon at the laser output for laser mode selection. Thus, larger effective values of the laser FSR were achieved, leading to higher-spatial frequency interferograms and therefore to more sensitive and accurate measurements. The quantitative evaluation of the interferograms was performed through the phase stepping technique (PST) and the phase map unwrapping was carried out through the Cellular-Automata method. For a given surface, shape measurements with different interferogram spatial frequencies were performed and compared, concerning measurement noise and visual inspection.

An effective wavelet method to detect and mitigate low-frequency multipath effects

To ensure high accuracy results from GPS relative positioning, the multipath effects have to be mitigated. Although the careful selection of antenna site and the use of especial antennas and receivers can minimize multipath, it cannot always be eliminated and frequently the residual multipath disturbance remains as the major error in GPS results. The high-frequency multipath from large delays can be attenuated by double difference (DD) denoising methods. But the low-frequency multipath from short delays is very difficult to be reduced or modeled. In this paper, it is proposed a method based on wavelet regression (WR), which can effectively detect and reduce the low-frequency multipath. The wavelet technique is firstly applied to decompose the DD residuals into the low-frequency bias and high-frequency noise components. The extracted bias components by WR are then directly applied to the DD observations to correct them from the trend. The remaining terms, largely characterized by the high-frequency measurement noise, are expected to give the best linear unbiased solutions from a least-squares (LS) adjustment. An experiment was carried out using objects placed close to the receiver antenna to cause, mainly, low-frequency multipath. The data were collected for two days to verify the multipath repeatability. The ground truth coordinates were computed with data collected in the absence of the reflector objects. The coordinates and ambiguity solution were compared with and without the multipath mitigation using WR. After mitigating the multipath, ambiguity resolution became more reliable and the coordinates were more accurate.

Distributed generation impact evaluation using a multi-objective tabu search

Distribution networks paradigm is changing currently requiring improved methodologies and tools for network analysis and planning. A relevant issue is analyzing the impact of the Distributed Generation penetration in passive networks considering different operation scenarios. Studying DG optimal siting and sizing the planner can identify the network behavior in presence of DG. Many approaches for the optimal DG allocation problem successfully used multi-objective optimization techniques. So this paper contributes to the fundamental stage of multi-objective optimization of finding the Pareto optimal solutions set. It is proposed the application of a Multi-objective Tabu Search and it was verified a better performance comparing to the NSGA-II method. © 2009 IEEE.

Linear scanning method based on the SAFT coarray

This work presents a method to obtain B-scan images based on linear array scanning and 2R-SAFT. Using this technique some advantages are obtained: the ultrasonic system is very simple; it avoids the grating lobes formation, characteristic in conventional SAFT; and subaperture size and focussing lens (to compensate emission-reception) can be adapted dynamically to every image point. The proposed method has been experimentally tested in the inspection of CFRP samples. © 2010 American Institute of Physics.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Coupling rate measurement of a novel multi-actuated piezoelectric device using optical interferometry

The class of piezoelectric actuators considered in this paper consists of a multi-flexible structure actuated by two or more piezoceramic devices that must generate different output displacements and forces at different specified points of the domain and in different directions. The devices were modeled by finite element using the software ANSYS and the topology optimization method. The following XY actuators were build to achieve maximum displacement in the X and Y directions with a minimum crosstalk between them. The actuator prototypes are composed of an aluminum structure, manufactured by using a wire Electrical Discharge Machining, which are bonded to rectangular PZT5A piezoceramic blocks by using epoxy resin. Multi-actuator piezoelectric device displacements can be measured by using optical interferometry, since it allows dynamic measurements in the kHz range, which is of the order of the first resonance frequency of these piezomechanisms. A Michelson-type interferometer, with a He-Ne laser source, is used to measure the displacement amplitudes in nanometric range. A new optical phase demodulation technique is applied, based on the properties of the triangular waveform drive voltage applied to the XY piezoelectric nanopositioner. This is a low-phase-modulation-depth-like technique that allows the rapid interferometer auto-calibration. The measurements were performed at 100 Hz frequency, and revealed that the device is linear voltage range utilized in this work. The ratio between the generated and coupled output displacements and the drive voltages is equal to 10.97 nm/V and 1.76 nm/V, respectively, which corresponds to a 16% coupling rate. © 2010 IEEE.

Decentralized AC power flow for real-time multi-TSO power system operation

This paper adjusts decentralized OPF optimization to the AC power flow problem in power systems with interconnected areas operated by diferent transmission system operators (TSO). The proposed methodology allows finding the operation point of a particular area without explicit knowledge of network data of the other interconnected areas, being only necessary to exchange border information related to the tie-lines between areas. The methodology is based on the decomposition of the first-order optimality conditions of the AC power flow, which is formulated as a nonlinear programming problem. To allow better visualization of the concept of independent operation of each TSO, an artificial neural network have been used for computing border information of the interconnected TSOs. A multi-area Power Flow tool can be seen as a basic building block able to address a large number of problems under a multi-TSO competitive market philosophy. The IEEE RTS-96 power system is used in order to show the operation and effectiveness of the decentralized AC Power Flow. ©2010 IEEE.

Distribution system restoration in a DG environment using a heuristic constructive multi-start algorithm

This paper proposes a heuristic constructive multi-start algorithm (HCMA) to distribution system restoration in real time considering distributed generators installed in the system. The problem is modeled as nonlinear mixed integer and considers the two main goals of the restoration of distribution networks: minimizing the number of consumers without power and the number of switching. The proposed algorithm is implemented in C++ programming language and tested using a large real-life distribution system. The results show that the proposed algorithm is able to provide a set of feasible and good quality solutions in a suitable time for the problem. © 2011 IEEE.

Mathematical decomposition technique applied to the probabilistic power flow problem

In this paper a framework based on the decomposition of the first-order optimality conditions is described and applied to solve the Probabilistic Power Flow (PPF) problem in a coordinated but decentralized way in the context of multi-area power systems. The purpose of the decomposition framework is to solve the problem through a process of solving smaller subproblems, associated with each area of the power system, iteratively. This strategy allows the probabilistic analysis of the variables of interest, in a particular area, without explicit knowledge of network data of the other interconnected areas, being only necessary to exchange border information related to the tie-lines between areas. An efficient method for probabilistic analysis, considering uncertainty in n system loads, is applied. The proposal is to use a particular case of the point estimate method, known as Two-Point Estimate Method (TPM), rather than the traditional approach based on Monte Carlo simulation. The main feature of the TPM is that it only requires resolve 2n power flows for to obtain the behavior of any random variable. An iterative coordination algorithm between areas is also presented. This algorithm solves the Multi-Area PPF problem in a decentralized way, ensures the independent operation of each area and integrates the decomposition framework and the TPM appropriately. The IEEE RTS-96 system is used in order to show the operation and effectiveness of the proposed approach and the Monte Carlo simulations are used to validation of the results. © 2011 IEEE.

Optimal energy generation with biomass of sugarcane harvest

The aim of this work is the application of the Interior Point and Branch and Bound methods in multiobjective optimization models related to sugarcane harvest residual biomass. These methods showed their viability to help on choosing the sugarcane planting varieties, searching to optimize cost and energy balance of harvest residual biomass, which have conflitant objectives. These methods provide satisfactory results, with fair computing performance and reliable and consistent solutions to the analyzed models. © 2011 IEEE.

State Dependent Riccati Equation (SDRE) control method applied in cancellation of a parametric resonance in a magnetically levitated body

Here, a simplified dynamical model of a magnetically levitated body is considered. The origin of an inertial Cartesian reference frame is set at the pivot point of the pendulum on the levitated body in its static equilibrium state (ie, the gap between the magnet on the base and the magnet on the body, in this state). The governing equations of motion has been derived and the characteristic feature of the strategy is the exploitation of the nonlinear effect of the inertial force associated, with the motion of a pendulum-type vibration absorber driven, by an appropriate control torque [4]. In the present paper, we analyzed the nonlinear dynamics of problem, discussed the energy transfer between the main system and the pendulum in time, and developed State Dependent Riccati Equation (SDRE) control design to reducing the unstable oscillatory movement of the magnetically levitated body to a stable fixed point. The simulations results showed the effectiveness of the (SDRE) control design. Copyright © 2011 by ASME.

Point vibration measurements for the detection of shallow-buried objects

A major UK initiative, entitled 'Mapping the Underworld', is seeking to address the serious social, environmental and economic consequences arising from an inability to locate accurately and comprehensively the buried utility service infrastructure without resorting to extensive excavations. Mapping the Underworld aims to develop and prove the efficacy of a multi-sensor device for accurate remote buried utility service detection, location and, where possible, identification. One of the technologies to be incorporated in the device is low-frequency vibro-acoustics, and application of this technique for detecting buried infrastructure is currently being investigated. Here, the potential for making a number of simple point vibration measurements in order to detect shallow-buried objects, in particular plastic pipes, is explored. Point measurements can be made relatively quickly without the need for arrays of surface sensors, which can be expensive, time-consuming to deploy, and sometimes impractical in congested areas. At low frequencies, the ground behaves as a simple single-degree-of-freedom (mass-spring) system with a well-defined resonance, the frequency of which will depend on the density and elastic properties of the soil locally. This resonance will be altered by the presence of a buried object whose properties differ from the surrounding soil. It is this behavior which can be exploited in order to detect the presence of a buried object, provided it is buried at a sufficiently shallow depth. The theoretical background is described and preliminary measurements are made both on a dedicated buried pipe rig and on the ground over a domestic waste pipe. Preliminary findings suggest that, for shallow-buried pipes, a measurement of this kind could be a quick and useful adjunct to more conventional methods of buried pipe detection. © 2012 Elsevier Ltd. All rights reserved.

The influence of subpixel measurement on digital camera calibration

The aim of this work is to evaluate the influence of point measurements in images, with subpixel accuracy, and its contribution in the calibration of digital cameras. Also, the effect of subpixel measurements in 3D coordinates of check points in the object space will be evaluated. With this purpose, an algorithm that allows subpixel accuracy was implemented for semi-automatic determination of points of interest, based on Fõrstner operator. Experiments were accomplished with a block of images acquired with the multispectral camera DuncanTech MS3100-CIR. The influence of subpixel measurements in the adjustment by Least Square Method (LSM) was evaluated by the comparison of estimated standard deviation of parameters in both situations, with manual measurement (pixel accuracy) and with subpixel estimation. Additionally, the influence of subpixel measurements in the 3D reconstruction was also analyzed. Based on the obtained results, i.e., on the quantification of the standard deviation reduction in the Inner Orientation Parameters (IOP) and also in the relative error of the 3D reconstruction, it was shown that measurements with subpixel accuracy are relevant for some tasks in Photogrammetry, mainly for those in which the metric quality is of great relevance, as Camera Calibration.