Adaptive Locomotion for Crossing a Moving Obstacle

Crossing moving obstacles requires different space-time adjustments compared with stationary obstacles. Our aim was to investigate gait spatial and temporal parameters in the approach and crossing phases of a moving obstacle. We hypothesized that obstacle speed affects gait parameters, which allow us to distinguish locomotor strategies. Ten young adults walked and stepped over an obstacle that crossed their way perpendicularly, under three obstacle conditions: control-stationary obstacle, slow (1.07 m/s) and fast speed (1.71 m/s) moving obstacles. Gait parameters were different between obstacle conditions, especially on the slow speed. In the fast condition, the participants adopted predictive strategies during the approach and crossing phases. In the slow condition, they used an anticipatory strategy in both phases. We conclude that obstacle speed affects the locomotor behavior and strategies were distinct in the obstacle avoidance phases.

Baroreflex control of heart rate in the broad-nosed caiman Caiman latirostris is temperature dependent

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Effects of Resinous Monomers Used in Restorative Dental Modeling on the Cohesive Strength of Composite Resin

Purpose: The purpose of this study was to evaluate the cohesive strength of the composite using different resinous monomers to lubricate instruments used in the Restorative Dental Modeling Insertion Technique (RDMIT).Materials and Methods: The composite specimens were made by using a prefabricated Teflon device. Different resinous monomers were used at the interface to lubricate the instruments, for a total of 72 specimens divided into 6 groups: 1. control group, no resinous monomer was used; 2. Composite Wetting Resin; 3. C & B Liquid; 4. Scotchbond Multi-Purpose Adhesive; 4. Adper Single Bond Adhesive; 6. Prime & Bond NT. Specimens were submitted to the circular area tensile test to evaluate the cohesive strength at the composite interfaces. Data were analyzed using ANOVA and Tukey's test (alpha = 0.05).Results: ANOVA showed a value of p < 0.0001, which indicated that there were significant differences among the groups. The means (SD) for the different groups were: Adper Single Bond Adhesive: 26 (12) a; control group: 28 (3) ab; Prime & Bond NT: 32 (12) ab; Composite Wetting Resin: 36 (9) abc; C&B Liquid: 38 (7) bc; Scotchbond Multi-Purpose Adhesive: 46 (10) c. Groups denoted with the same letters were not significantly different. Only Scotchbond Multi-Purpose Adhesive, used for direct restorations, had a statistically significantly higher bond strength than the control group, Adper Single Bond Adhesive, and Prime & Bond NT. Adper Single Bond with Adhesive showed a statistically significantly lower mean value than C & B Liquid.Conclusion: The results of this study indicate that the resinous monomers used for lubricating the instruments in the RDMIT did not alter the mechanical properties of the composite, and therefore did not reduce the cohesive bond strength at the composite interfaces.

Chaos control of a nonlinear oscillator with shape memory alloy using an optimal linear control: Part I: Ideal energy source

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Phase-Locked loops lock-in range in Frequency Modulated-Atomic Force Microscope nonlinear control system

Since the mid 1980s the Atomic Force Microscope is one the most powerful tools to perform surface investigation, and since 1995 Non-Contact AFM achieved true atomic resolution. The Frequency-Modulated Atomic Force Microscope (FM-AFM) operates in the dynamic mode, which means that the control system of the FM-AFM must force the micro-cantilever to oscillate with constant amplitude and frequency. However, tip-sample interaction forces cause modulations in the microcantilever motion. A Phase-Locked loop (PLL) is used to demodulate the tip-sample interaction forces from the microcantilever motion. The demodulated signal is used as the feedback signal to the control system, and to generate both topographic and dissipation images. As a consequence, a proper design of the PLL is vital to the FM-AFM performance. In this work, using bifurcation analysis, the lock-in range of the PLL is determined as a function of the frequency shift (Q) of the microcantilever and of the other design parameters, providing a technique to properly design the PLL in the FM-AFM system. (C) 2011 Elsevier B.V. All rights reserved.

Phase-Locked Loop design applied to frequency-modulated atomic force microscope

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

On control and synchronization in chaotic and hyperchaotic systems via linear feedback control

This paper presents the control and synchronization of chaos by designing linear feedback controllers. The linear feedback control problem for nonlinear systems has been formulated under optimal control theory viewpoint. Asymptotic stability of the closed-loop nonlinear system is guaranteed by means of a Lyapunov function which can clearly be seen to be the solution of the Hamilton-Jacobi-Bellman equation thus guaranteeing both stability and optimality. The formulated theorem expresses explicitly the form of minimized functional and gives the sufficient conditions that allow using the linear feedback control for nonlinear system. The numerical simulations were provided in order to show the effectiveness of this method for the control of the chaotic Rossler system and synchronization of the hyperchaotic Rossler system. (C) 2007 Elsevier B.V. All rights reserved.

An Optimal Linear Control Design for Nonlinear Systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Suggestion of an inverse relationship between perception of occupational risks and work-related injuries

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multivalued adaptive neuro-fuzzy controller for robot vehicle - art. no. 1406

Robotic vehicle navigation in unstructured and uncertain environments is still a challenge. This paper presents the implementation of a multivalued neurofuzzy controller for autonomous ground vehicle (AGVs) in indoor environments. The control system consists of a hierarchy of mobile robot using multivalued adaptive neuro-fuzzy inference system behaviors.

Constrained optimization model for the design of an adaptive (X)over-bar chart

An economic-statistical model is developed for variable parameters (VP) (X) over bar charts in which all design parameters vary adaptively, that is, each of the design parameters (sample size, sampling interval and control-limit width) vary as a function of the most recent process information. The cost function due to controlling the process quality through a VP (X) over bar chart is derived. During the optimization of the cost function, constraints are imposed on the expected times to signal when the process is in and out of control. In this way, required statistical properties can be assured. Through a numerical example, the proposed economic-statistical design approach for VP (X) over bar charts is compared to the economic design for VP (X) over bar charts and to the economic-statistical and economic designs for fixed parameters (FP) (X) over bar charts in terms of the operating cost and the expected times to signal. From this example, it is possible to assess the benefits provided by the proposed model. Varying some input parameters, their effect on the optimal cost and on the optimal values of the design parameters was analysed.

Modeling thermal conductivity, specific heat, and density of milk: A neural network approach

The accurate determination of thermophysical properties of milk is very important for design, simulation, optimization, and control of food processing such as evaporation, heat exchanging, spray drying, and so forth. Generally, polynomial methods are used for prediction of these properties based on empirical correlation to experimental data. Artificial neural networks are better Suited for processing noisy and extensive knowledge indexing. This article proposed the application of neural networks for prediction of specific heat, thermal conductivity, and density of milk with temperature ranged from 2.0 to 71.0degreesC, 72.0 to 92.0% of water content (w/w), and 1.350 to 7.822% of fat content (w/w). Artificial neural networks presented a better prediction capability of specific heat, thermal conductivity, and density of milk than polynomial modeling. It showed a reasonable alternative to empirical modeling for thermophysical properties of foods.

An adaptive chart for monitoring the process mean and variance

Traditionally, an (X) over bar chart is used to control the process mean and an R chart is used to control the process variance. However, these charts are not sensitive to small changes in the process parameters. The adaptive ($) over bar and R charts might be considered if the aim is to detect small disturbances. Due to the statistical character of the joint (X) over bar and R charts with fixed or adaptive parameters, they are not reliable in identifing the nature of the disturbance, whether it is one that shifts the process mean, increases the process variance, or leads to a combination of both effects. In practice, the speed with which the control charts detect process changes may be more important than their ability in identifying the nature of the change. Under these circumstances, it seems to be advantageous to consider a single chart, based on only one statistic, to simultaneously monitor the process mean and variance. In this paper, we propose the adaptive non-central chi-square statistic chart. This new chart is more effective than the adaptive (X) over bar and R charts in detecting disturbances that shift the process mean, increase the process variance, or lead to a combination of both effects. Copyright (c) 2006 John Wiley & Sons, Ltd.

Synthetic control chart for monitoring the pprocess mean and variance

In this article, we consider the synthetic control chart with two-stage sampling (SyTS chart) to control the process mean and variance. During the first stage, one item of the sample is inspected; if its value X, is close to the target value of the process mean, then the sampling is interrupted. Otherwise, the sampling goes on to the second stage, where the remaining items are inspected and the statistic T = Sigma [x(i) - mu(0) + xi sigma(0)](2) is computed taking into account all items of the sample. The design parameter is function of X-1. When the statistic T is larger than a specified value, the sample is classified as nonconforming. According to the synthetic procedure, the signal is based on Conforming Run Length (CRL). The CRL is the number of samples taken from the process since the previous nonconforming sample until the occurrence of the next nonconforming sample. If the CRL is sufficiently small, then a signal is generated. A comparative study shows that the SyTS chart and the joint X and S charts with double sampling are very similar in performance. However, from the practical viewpoint, the SyTS chart is more convenient to administer than the joint charts.

Simplified architecture of a neurofuzzy controller applied on industrial systems for fluid flow control

This work presents a simplified architecture of a neurofuzzy controller for general purpose applications that tries to minimize the processing used in the several stages of hazy modeling of systems. The basic procedures of fuzzification and defuzzification are simplified to the maximum while the inference procedures are computed in a private way. The simplified architecture allows a fast and easy configuration of the neurofuzzy controller and the structuring rules that define the control actions is automatic. Th controller's Limits and performance are standardized and the control actions are previously calculated. For application, the industrial systems of fluid flow control will be considered.