Experimental investigation on adaptive robust controller designs applied to a free-floating space manipulator

This paper aims to formulate and investigate the application of various nonlinear H(infinity) control methods to a fiee-floating space manipulator subject to parametric uncertainties and external disturbances. From a tutorial perspective, a model-based approach and adaptive procedures based on linear parametrization, neural networks and fuzzy systems are covered by this work. A comparative study is conducted based on experimental implementations performed with an actual underactuated fixed-base planar manipulator which is, following the DEM concept, dynamically equivalent to a free-floating space manipulator. (C) 2011 Elsevier Ltd. All rights reserved.

Bidimensional codes recorded on an oxide glass surface using a continuous wave CO(2) laser

Surface heat treatment in glasses and ceramics, using CO(2) lasers, has attracted the attention of several researchers around the world due to its impact in technological applications, such as lab-on-a-chip devices, diffraction gratings and microlenses. Microlens fabrication on a glass surface has been studied mainly due to its importance in optical devices (fiber coupling, CCD signal enhancement, etc). The goal of this work is to present a systematic study of the conditions for microlens fabrications, along with the viability of using microlens arrays, recorded on the glass surface, as bidimensional codes for product identification. This would allow the production of codes without any residues (like the fine powder generated by laser ablation) and resistance to an aggressive environment, such as sterilization processes. The microlens arrays were fabricated using a continuous wave CO(2) laser, focused on the surface of flat commercial soda-lime silicate glass substrates. The fabrication conditions were studied based on laser power, heating time and microlens profiles. A He-Ne laser was used as a light source in a qualitative experiment to test the viability of using the microlenses as bidimensional codes.

Microstructure and mechanical properties of laser-welded joints of TWIP and TRIP steels

With the aim of investigating a laser-welded dissimilar joint of TWIP and TRIP steel sheets, the microstructure was characterized by means of OM, SEM, and EBSD to differentiate the fusion zone, heat-affected zone, and the base material. OIM was used to differentiate between ferritic, bainitic, and martensitic structures. Compositions were measured by means of optical emission spectrometry and EDX to evaluate the effect of manganese segregation. Microhardness measurements and tensile tests were performed to evaluate the mechanical properties of the joint. Residual stresses and XRD phase quantification were used to characterize the weld. Grain coarsening and martensitic areas were found in the fusion zone, and they had significant effects on the mechanical properties of the weld. The heat-affected zone of the TRIP steel and the corresponding base material showed considerable differences in the microstructure and properties. (C) 2009 Elsevier B.V. All rights reserved.

Adaptive Approach for a Maximum Entropy Algorithm in Ecological Niche Modeling

This paper presents an Adaptive Maximum Entropy (AME) approach for modeling biological species. The Maximum Entropy algorithm (MaxEnt) is one of the most used methods in modeling biological species geographical distribution. The approach presented here is an alternative to the classical algorithm. Instead of using the same set features in the training, the AME approach tries to insert or to remove a single feature at each iteration. The aim is to reach the convergence faster without affect the performance of the generated models. The preliminary experiments were well performed. They showed an increasing on performance both in accuracy and in execution time. Comparisons with other algorithms are beyond the scope of this paper. Some important researches are proposed as future works.

A Procedure for Semantic Querying in the Adaptive Formalism

This paper contains a new proposal for the definition of the fundamental operation of query under the Adaptive Formalism, one capable of locating functional nuclei from descriptions of their semantics. To demonstrate the method`s applicability, an implementation of the query procedure constrained to a specific class of devices is shown, and its asymptotic computational complexity is discussed.

Evaluation of Adaptive Genetic Algorithm to Environmental Modeling of Peponapis and Cucurbita

This paper presents a free software tool that supports the next-generation Mobile Communications, through the automatic generation of models of components and electronic devices based on neural networks. This tool enables the creation, training, validation and simulation of the model directly from measurements made on devices of interest, using an interface totally oriented to non-experts in neural models. The resulting model can be exported automatically to a traditional circuit simulator to test different scenarios.

Placement over containers with fixed dimensions solved with adaptive neighborhood simulated annealing

This work deals with the problem of minimizing the waste of space that occurs on a rotational placement of a set of irregular bi-dimensional items inside a bi-dimensional container. This problem is approached with a heuristic based on Simulated Annealing (SA) with adaptive neighborhood. The objective function is evaluated in a constructive approach, where the items are placed sequentially. The placement is governed by three different types of parameters: sequence of placement, the rotation angle and the translation. The rotation applied and the translation of the polygon are cyclic continuous parameters, and the sequence of placement defines a combinatorial problem. This way, it is necessary to control cyclic continuous and discrete parameters. The approaches described in the literature deal with only type of parameter (sequence of placement or translation). In the proposed SA algorithm, the sensibility of each continuous parameter is evaluated at each iteration increasing the number of accepted solutions. The sensibility of each parameter is associated to its probability distribution in the definition of the next candidate.

Mechanical strength evaluation for Nd-YAG laser and electric resistance spot weld (ERSW) joint under multiaxial loading

This work presents a comparison between laser weld (LBW) and electric resistance spot weld (ERSW) processes used for assemblies of components in a body-in-white (BIW) at a world class automotive industry. It is carried out by evaluating the mechanical strength modeled both by experimental and numerical methods. An ""Arcan"" multiaxial test was designed and manufactured in order to enable 0 degrees, 45 degrees and 90 degrees directional loadings. The welded specimens were uncoated low carbon steel sheets (S-y = 170 MPa) used currently at the automotive industry, with two different thicknesses: 0.80 and 1.20 mm. A numerical analysis was carried out using the finite element method (FEM) through LS-DYNA code. (c) 2007 Elsevier B.V. All rights reserved.

Methods of Fourier optics in digital holographic microscopy

In this paper, processing methods of Fourier optics implemented in a digital holographic microscopy system are presented. The proposed methodology is based on the possibility of the digital holography in carrying out the whole reconstruction of the recorded wave front and consequently, the determination of the phase and intensity distribution in any arbitrary plane located between the object and the recording plane. In this way, in digital holographic microscopy the field produced by the objective lens can be reconstructed along its propagation, allowing the reconstruction of the back focal plane of the lens, so that the complex amplitudes of the Fraunhofer diffraction, or equivalently the Fourier transform, of the light distribution across the object can be known. The manipulation of Fourier transform plane makes possible the design of digital methods of optical processing and image analysis. The proposed method has a great practical utility and represents a powerful tool in image analysis and data processing. The theoretical aspects of the method are presented, and its validity has been demonstrated using computer generated holograms and images simulations of microscopic objects. (c) 2007 Elsevier B.V. All rights reserved.

Simulated annealing with adaptive neighborhood: A case study in off-line robot path planning

Simulated annealing (SA) is an optimization technique that can process cost functions with degrees of nonlinearities, discontinuities and stochasticity. It can process arbitrary boundary conditions and constraints imposed on these cost functions. The SA technique is applied to the problem of robot path planning. Three situations are considered here: the path is represented as a polyline; as a Bezier curve; and as a spline interpolated curve. In the proposed SA algorithm, the sensitivity of each continuous parameter is evaluated at each iteration increasing the number of accepted solutions. The sensitivity of each parameter is associated to its probability distribution in the definition of the next candidate. (C) 2010 Elsevier Ltd. All rights reserved.

Adaptive Carrier Tracking for Mars to Earth Communications During Entry, Descent, and Landing

We propose a robust and low complexity scheme to estimate and track carrier frequency from signals traveling under low signal-to-noise ratio (SNR) conditions in highly nonstationary channels. These scenarios arise in planetary exploration missions subject to high dynamics, such as the Mars exploration rover missions. The method comprises a bank of adaptive linear predictors (ALP) supervised by a convex combiner that dynamically aggregates the individual predictors. The adaptive combination is able to outperform the best individual estimator in the set, which leads to a universal scheme for frequency estimation and tracking. A simple technique for bias compensation considerably improves the ALP performance. It is also shown that retrieval of frequency content by a fast Fourier transform (FFT)-search method, instead of only inspecting the angle of a particular root of the error predictor filter, enhances performance, particularly at very low SNR levels. Simple techniques that enforce frequency continuity improve further the overall performance. In summary we illustrate by extensive simulations that adaptive linear prediction methods render a robust and competitive frequency tracking technique.

Transient and Steady-State Analysis of the Affine Combination of Two Adaptive Filters

In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance. Good agreement between analysis and simulation results is always observed.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

MEMS-based incandescent microlamps for integrated optics applications

In this work we present the fabrication and operation of incandescent microlamps for integrated optics applications. This microlamp emits white and infrared light from a chromium resistor embedded in a free-standing silicon oxynitride (SiO(x)N(y)) cantilever that can be coupled to an optical waveguide. In fact, the chromium resistor is sandwiched between layers of SiO(x)N(y) that isolate it from the atmosphere, while electric current heats the resistor to incandescent temperatures. The same SiO(x)N(y) material used in the microlamp fabrication is also used to produce the optical waveguides to allow a monolithic integration of light source and optical circuit. Front-side bulk micromachining of the silicon substrate in potassium hydroxide (KOH) solution is used to fabricate the cantilevers that thermally isolate the resistors from the substrate, thus reducing the heat transfer and the current required to light the lamp.

Improving the tracking capability of adaptive filters via convex combination

As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.