Neural network-based H(infinity) control for fully actuated and underactuated cooperative manipulators

This paper develops H(infinity) control designs based on neural networks for fully actuated and underactuated cooperative manipulators. The neural networks proposed in this paper only adapt the uncertain dynamics of the robot manipulators. They work as a complement of the nominal model. The H(infinity) performance index includes the position errors as well the squeeze force errors between the manipulator end-effectors and the object, which represents a complete disturbance rejection scenario. For the underactuated case, the squeeze force control problem is more difficult to solve due to the loss of some degrees of manipulator actuation. Results obtained from an actual cooperative manipulator, which is able to work as a fully actuated and an underactuated manipulator, are presented. (C) 2008 Elsevier Ltd. All rights reserved.

Artificial neural networks analysis of Sao Paulo subway tunnel settlement data

Artificial neural networks have been used to analyze a number of engineering problems, including settlement caused by different tunneling methods in various types of ground mass. This paper focuses on settlement over shotcrete- supported tunnels on Sao Paulo subway line 2 (West Extension) that were excavated in Tertiary sediments using the sequential excavation method. The adjusted network is a good tool for predicting settlement above new tunnels to be excavated in similar conditions. The influence of network training parameters on the quality of results is also discussed. (C) 2007 Elsevier Ltd. All rights reserved.

Nitrogen removal in a sequencing batch biofilm reactor with liquid circulation: Effect of feed strategy and carbon source in the denitrifying step

Ammonium nitrogen removal from a synthetic wastewater by nitrification and denitrification processes were performed in a sequencing batch biofilm reactor containing immobilized biomass on polyurethane foam with circulation of the liquid-phase. It was analyzed the effect of four external carbon sources (ethanol, acetate, carbon synthetic medium and methanol) acting as electron donors in the denitrifying process. The experiments were conducted with intermittent aeration and operated at 30+/-1 degrees C in 8-h cycles. The synthetic wastewater (100 mgCOD/L and 50 mgNH(4)(+)-N/L) was added batch-wise, while the external carbon sources were added fed-batch-wise during the periods where aeration was suspended. Ammonium nitrogen removal efficiencies obtained were 95.7, 94.3 and 97.5% for ethanol, acetate and carbon synthetic medium, respectively. As to nitrite, nitrate and ammonium nitrogen effluent concentrations, the results obtained were, respectively: 0.1, 5.7 and 1.4 mg/L for ethanol; 0.2, 4.1 and 1.8 mg/L for acetate and 0.2, 6.7 and 0.8 for carbon synthetic medium. On the other hand using methanol, even at low concentrations (50% of the stoichiometric value calculated for complete denitrification), resulted in increasing accumulation of nitrate and ammonium nitrogen in the effluent over time.

Anaerobic treatment of sulfate-rich wastewater in an anaerobic sequential batch reactor (AnSBR) using butanol as the carbon source

Biological sulfate reduction was studied in a laboratory-scale anaerobic sequential batch reactor (14 L) containing mineral coal for biomass attachment. The reactor was fed industrial wastewater with increasingly high sulfate concentrations to establish its application limits. Special attention was paid to the use of butanol in the sulfate reduction that originated from melamine resin production. This product was used as the main organic amendment to support the biological process. The reactor was operated for 65 cycles (48 h each) at sulfate loading rates ranging from 2.2 to 23.8 g SO(4)(2-)/cycle, which corresponds to sulfate concentrations of 0.25, 0.5,1.0, 2.0 and 3.0 g SW(4)(2-)L(-1). The sulfate removal efficiency reached 99% at concentrations of 0.25, 0.5 and 1.0 g SO(4)(2-)L(-1). At higher sulfate concentrations (2.0 and 3.0 g SO(4)(2-)L(-1)), the sulfate conversion remained in the range of 71-95%. The results demonstrate the potential applicability of butanol as the carbon source for the biological treatment of sulfate in an anaerobic batch reactor. (C) 2011 Elsevier Ltd. All rights reserved.

Influence of carbon source and inoculum type on anaerobic biomass adhesion on polyurethane foam in reactors fed with acid mine drainage

This paper analyzes the influence of carbon source and inoculum origin on the dynamics of biomass adhesion to an inert support in anaerobic reactors fed with acid mine drainage. Formic acid, lactic acid and ethanol were used as carbon sources. Two different inocula were evaluated: one taken from an UASB reactor and other from the sediment of a uranium mine. The values of average colonization rates and the maximum biomass concentration (C(max)) were inversely proportional to the number of carbon atoms in each substrate. The highest C(max) value (0.35 g TVS g(-1) foam) was observed with formic acid and anaerobic sludge as inoculum. Maximum colonization rates (v(max)) were strongly influenced by the type of inoculum when ethanol and lactic acid were used. For both carbon sources, the use of mine sediment as inoculum resulted in a v(max) of 0.013 g TVS g(-1) foam day(-1), whereas 0.024 g TVS g(-1) foam day(-1) was achieved with anaerobic sludge. (C) 2011 Elsevier Ltd. All rights reserved.

Transmission lines distance protection using artificial neural networks

This work presents the development and implementation of an artificial neural network based algorithm for transmission lines distance protection. This algorithm was developed to be used in any transmission line regardless of its configuration or voltage level. The described ANN-based algorithm does not need any topology adaptation or ANN parameters adjustment when applied to different electrical systems. This feature makes this solution unique since all ANN-based solutions presented until now were developed for particular transmission lines, which means that those solutions cannot be implemented in commercial relays. (c) 2011 Elsevier Ltd. All rights reserved.

BIOLOGICAL NITROGEN REMOVAL OVER NITRITATION/DENITRITATION USING PHENOL AS CARBON SOURCE

A laboratory scale activated sludge sequencing batch reactor was operated in order to obtain total removal of influent ammonia (200; 300 and 500 mg NH(3)-N.L(-1)) with sustained nitrite accumulation at the end of the aerobic stages with phenol (1,000 mg C(6)H(5)OH.L(-1)) as the carbon source for denitrifying microorganisms during the anoxic stages. Ammonia removal above 95% and ratios of (NO(2)(-)-N / (NO(2)(-)-N + NO(3)(-)-N)) ranging from 89 to 99% were obtained by controlling the dissolved oxygen concentration (1.0 mg O(2).L(-1)) and the pH value of 8.3 during the aerobic stages. Phenol proved to be an adequate source of carbon for nitrogen removal via nitrite with continuous feeding throughout part of the anoxic stage. Nitrite concentrations greater than 70.0 mg NO(2)(-)-N.L(-1) inhibited the biological denitritation process.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

Treatment of Aqueous Effluents Containing Phenol by the O(3), O(3)-UV, and O(3)-H(2)O(2) Processes: Experimental Study and Neural Network Modeling

In this work, the oxidation of the model pollutant phenol has been studied by means of the O(3), O(3)-UV, and O(3)-H(2)O(2) processes. Experiments were carried out in a fed-batch system to investigate the effects of initial dissolved organic carbon concentration, initial, ozone concentration in the gas phase, the presence or absence of UVC radiation, and initial hydrogen peroxide concentration. Experimental results were used in the modeling of the degradation processes by neural networks in order to simulate DOC-time profiles and evaluate the relative importance of process variables.

USE OF SOLAR ENERGY IN THE TREATMENT OF WATER CONTAMINATED WITH PHENOL BY PHOTOCHEMICAL PROCESSES

The solar driven photo-Fenton process for treating water containing phenol as a contaminant has been evaluated by means of pilot-scale experiments with a parabolic trough solar reactor (PTR). The effects of Fe(II) (0.04-1.0 mmol L(-1)), H(2)O(2) (7-270 mmol L(-1)), initial phenol concentration (100 and 500 mg C L(-1)), solar radiation, and operation mode (batch and fed-batch) on the process efficiency were investigated. More than 90% of the dissolved organic carbon (DOC) was removed within 3 hours of irradiation or less, a performance equivalent to that of artificially-irradiated reactors, indicating that solar light can be used either as an effective complementary or as an alternative source of photons for the photo-Fenton degradation process. A non-linear multivariable model based on a neural network was fit to the experimental results of batch-mode experiments in order to evaluate the relative importance of the process variables considered on the DOC removal over the reaction time. This included solar radiation, which is not a controlled variable. The observed behavior of the system in batch-mode was compared with fed-batch experiments carried out under similar conditions. The main contribution of the study consists of the results from experiments under different conditions and the discussion of the system behavior. Both constitute important information for the design and scale-up of solar radiation-based photodegradation processes.

Network of phase-locking oscillators and a possible model for neural synchronization

In order to model the synchronization of brain signals, a three-node fully-connected network is presented. The nodes are considered to be voltage control oscillator neurons (VCON) allowing to conjecture about how the whole process depends on synaptic gains, free-running frequencies and delays. The VCON, represented by phase-locked loops (PLL), are fully-connected and, as a consequence, an asymptotically stable synchronous state appears. Here, an expression for the synchronous state frequency is derived and the parameter dependence of its stability is discussed. Numerical simulations are performed providing conditions for the use of the derived formulae. Model differential equations are hard to be analytically treated, but some simplifying assumptions combined with simulations provide an alternative formulation for the long-term behavior of the fully-connected VCON network. Regarding this kind of network as models for brain frequency signal processing, with each PLL representing a neuron (VCON), conditions for their synchronization are proposed, considering the different bands of brain activity signals and relating them to synaptic gains, delays and free-running frequencies. For the delta waves, the synchronous state depends strongly on the delays. However, for alpha, beta and theta waves, the free-running individual frequencies determine the synchronous state. (C) 2011 Elsevier B.V. All rights reserved.

Using Reverberation to Improve Range and Elevation Discrimination for Small Array Sound Source Localization

Sound source localization (SSL) is an essential task in many applications involving speech capture and enhancement. As such, speaker localization with microphone arrays has received significant research attention. Nevertheless, existing SSL algorithms for small arrays still have two significant limitations: lack of range resolution, and accuracy degradation with increasing reverberation. The latter is natural and expected, given that strong reflections can have amplitudes similar to that of the direct signal, but different directions of arrival. Therefore, correctly modeling the room and compensating for the reflections should reduce the degradation due to reverberation. In this paper, we show a stronger result. If modeled correctly, early reflections can be used to provide more information about the source location than would have been available in an anechoic scenario. The modeling not only compensates for the reverberation, but also significantly increases resolution for range and elevation. Thus, we show that under certain conditions and limitations, reverberation can be used to improve SSL performance. Prior attempts to compensate for reverberation tried to model the room impulse response (RIR). However, RIRs change quickly with speaker position, and are nearly impossible to track accurately. Instead, we build a 3-D model of the room, which we use to predict early reflections, which are then incorporated into the SSL estimation. Simulation results with real and synthetic data show that even a simplistic room model is sufficient to produce significant improvements in range and elevation estimation, tasks which would be very difficult when relying only on direct path signal components.

Analysis of source-follower buffers implemented with graded-channel SOI nMOSFETs operating at cryogenic temperatures

This work studies the operation of source-follower buffers implemented with standard and graded-channel (GC) fully depleted (FD) SCI nMOSFETs at low temperatures. The analysis is performed by comparing the voltage gain of buffers implemented with GC and standard SOI nMOS transistors considering devices with the same mask channel length and same effective channel length. It is shown that the use of GC devices allows for achieving improved gain in all inversion levels in a wide range of temperatures. In addition, this improvement increases as temperature is reduced. It is shown that GC transistors can provide virtually constant gain, while for standard devices, the gain departs from the maximum value depending on the temperature and inversion level imposed by the bias current and input voltage. Two-dimensional numerical simulations were performed in order to study the reasons for the enhanced gain of GC MOSFETs at low temperatures. (C) 2009 Elsevier Ltd. All rights reserved.

Nonlinear Interactions in a Piezoceramic Bar Transducer Powered by a Vacuum Tube Generated by a Nonideal Source

Interactions between the oscillations of piezoceramic transducer and the mechanism of as excitation-the generator of the electric current of limited power-supply-are analyzed in this paper In practical situations, the dynamics of the forcing function on a vibrating system cannot be considered as given a priori, and it must be taken as a consequence of the dynamics of the whole system. In other words, the forcing source has limited power as that provided by a dc motor for an example, and thus its own dynamics is influenced by that of the vibrating system being forced. This increases the number of degrees of freedom of the problem, and it is called a nonideal problem. In this work, we present certain phenomena as Sommerfeld effect, jump, saturation, and stability, through the influences of the parameters of the governing equations motion. [DOI: 10.1115/1.3007909]

Advantages of graded-channel SOI nMOSFETs for application as source-follower analog buffer

In this work the performance of graded-channel (CC) SOI MOSFETs operating as source-follower buffers is presented. The experimental analysis is performed by comparing the gain and linearity of buffers implemented with CC and standard SOI MOS devices considering the same mask dimensions. It is shown that by using CC devices, buffer gain very close to the theoretical limit can be achieved, with improved linearity, while for standard devices the gain departs from the theoretical value depending on the inversion level imposed by the bias current and input voltage. Two-dimensional numerical simulations were performed in order to confirm some hypotheses proposed to explain the gain behavior observed in the experimental data. By using numerical simulations the channel length has been varied, showing that the gain of buffers implemented with CC devices remains close to the theoretical limit even when short-channel devices are adopted. It has also been shown that the length of a source-follower buffer using CC devices can be reduced by a factor of 5, in comparison with a standard Sol MOSFET, without gain loss or linearity degradation. (C) 2008 Elsevier Ltd. All rights reserved.