Scielo RSS <![CDATA[Latin American applied research]]> vol. 35 num. 2 lang. es <![CDATA[SciELO Logo]]> <![CDATA[A model for induction motors with non-uniform air-gap]]> Equations to calculate inductances of induction motors, considering non-uniform air-gap, are proposed. The analyzed air-gap variations are static and dynamic eccentricity and stator slots. The equations for inductance calculation, obtained from the modified winding functions and the energy stored in the air-gap, allow considering the effect of rotor bar skewing. Experimental results that validate the proposed method are presented. <![CDATA[Development of a state feedback controller for the synchronouns buck converter]]> A digital control algorithm for a current-mode (CM) and a voltage-mode (VM) synchronous buck converter (SBC) is developed. In both cases, the design leads to a stable controller, even for a duty cycle larger than 50%. The desired output voltage and the transient response can be independently specified. Moreover, zero steady-state error in the output voltage can be obtained with the aid of additional dynamics. In both cases, the specification is done by pole placement using complete state feedback. A discrete-time model is used to design the feedback gains. Both the stability and the small-signal transient response are analyzed. In another paper (Oliva et al., 2003) the control algorithms are experimentally validated with a DSP-controlled SBC. <![CDATA[Reduction of total harmonic distortion in power inverters]]> The output voltage of PWM power inverters shows harmonic distortion due to several causes; the main ones are the modulation algorithm, nonlinearities in the output filter, dead times, voltage drops across the switches and modulation of the dc bus voltage. The distortion is more evident when using low dc bus voltages. As a result, motors driven by these inverters have important torque pulsations. This work proposes to reduce the distortion produced by dead times and voltage drops across the switches using a simple algorithm that recalculates the width of each PWM pulse, while preserving the ideal area. By simulation, the THD was reduced from 18% to 0.29% in a single-phase inverter. The proposed algorithm only needs products and sums, so it is suitable for being implemented on a DSP with a very low processing load. <![CDATA[Performance evaluation of maximum likelihood sequence estimation receivers in lightwave systems with optical amplifiers]]> Maximum likelihood sequence estimation (MLSE) has been proposed in earlier literature to combat the effects of nonlinear dispersion in intensity modulation/direct detection (IM/DD) optical channels. In this paper, we develop a theory of the bit error rate (BER) of MLSE-based IM/DD receivers operating in the presence of nonlinear dispersion and amplified spontaneous emission (ASE) noise. We focus on long haul or metro links spanning several hundred kilometers of single mode fibers with optical amplifiers. Numerical results show a close agreement between the predictions of the theory and computer simulations. <![CDATA[Reduced complexity maximum likelihood sequence estimator for high-speed fiber optic communication systems]]> In this paper we present a new reduced complexity maximum likelihood sequence detector for intensity modulation / direct detection (IM/DD) fiber optic systems. The proposed detector takes into account the presence of thermal and amplified spontaneous emission (ASE) noise. The results presented here show a negligible performance degradation from the optimum receiver, while implementation complexity is significantly reduced. The mathematical models derived in this paper are attractive for the design and analysis of very high speed optical receivers. <![CDATA[The hybrid metric map: a solution for precision farming]]> This work presents a specific application of a novel map representation, the Hybrid Metric Map. This representation allows a consistent autonomous localization and simultaneously the synthesis of a detailed description of the environment where the robot or vehicle operates. There are many applications where an autonomous vehicle senses environment properties that are not necessarily used for the localization process. Precision agriculture is a special case of this. The proposed algorithm is able to fuse a large amount of information for the environment description and simultaneously estimate the vehicle position. <![CDATA[Cardiovascular engineering: modelization of ventricular-arterial interaction in systemic and pulmonary circulation]]> The heart pumps pressure and flow signals with relevant amount of frequency components cushioned along the arterial system. A pressure transfer function approach was designed to evaluate the Ventricular-Arterial Interaction. Two transfer functions were calculated relating ventricular to arterial pressure. A frequency response analysis followed the time-domain adaptation. Additionally, a viscoelastic model was proposed to characterize the arterial wall mechanical behavior, using the elastic (E) and viscous (h ) moduli. Six merino sheep were instrumented and anesthetized. Pressure measurements were registered in both ventricles, in aorta and in the pulmonary artery. Diameters (sonomicrometry) were measured in both arteries. The frequency transfer function asymptotic negative slope, describing the attenuation within the dynamic range, resulted 5 times greater in aorta (p<0.05), what presents the systemic as a more selective circuit than the pulmonary. E and h resulted higher (p<0.05) in aorta than in the pulmonary artery whereas E/h was similar. The viscoelastic results might indicate a similar segmental (unit-cell) response in both arteries. The enhanced cushioning ability of the left circuit with respect to the right, might be understood as a more selective vascular filtering system. This filtering performance might be related to the functional length of unit-cell responses along the systemic circulation. <![CDATA[Use of GPS carrier phase double differences]]> GPS carrier phase single and double difference characteristics are studied. Residual errors obtained from experimental results using independent commercial receivers for two antennas are analyzed. The potential of double differences for vehicle attitude estimation using a multiple antenna configuration with independent receivers is demonstrated. Receiver data synchronization is also given special attention. <![CDATA[Sampled-data minimum variance filtering]]> This paper deals with the optimal solution to the sampled-data minimum variance filtering problem for linear systems with noise in the states and in the measurements. The solution is derived in the time-domain by using a fast sampling zero-order hold input discretization of the continuous time systems together with a lifting technique. The original sampled-data system is transformed into an equivalent LTI discrete-time system with infinite-dimensional input-output space. However, the designed filter is finite-dimensional. We derive both the existence conditions and the explicit expression of the desired filter and provide an illustrative numerical example. <![CDATA[Digital communication interface for an automotive application]]> This paper presents the design and implementation of a digital communication interface between a Motor Drive Controller (MDC) and a digital network supervisor. This work is part of the DOE/CARAT project "Integrated Controllers for Automotive Auxiliary Electric Motors", being performed between the University of Arkansas and at GEA (Applied Electronics Group), National University of Rio Cuarto. The Controller Area Network (CAN) is the digital communication protocol of choice for automotive applications. The MDC was implemented using a Digital Signal Processor (DSP) and the network supervisor using a standard personal computer (PC) with a CAN communication board. <![CDATA[Discrete event control of time-varying plants]]> This paper studies the use of Quantized State Control (QSC) in Time-Varying (TV) plants. Making use of a Lyapunov analysis, the stability properties of Time Invariant QSC are extended to the non- stationary case. Then, based on the resulting stability theorem, a design algorithm is developed. Finally, the use of this algorithm -which allows the design of QSC controllers according to stability and convergence speed features- is shown with the design and the simulation of an illustrative example. <![CDATA[A new estimator based on maximum entropy]]> In this paper, we propose a new formulation of the classical Good-Turing estimator for n-gram language models. The new approach is based on defining a dynamic model for language production. Instead of assuming a fixed probability distribution of occurrence of an n-gram on the whole text, we propose a maximum entropy approximation of a time varying distribution. This approximation led us to a new distribution, which in turn is used to calculate expectations of the Good-Turing estimator. This defines a new estimator that we call Maximum Entropy Good-Turing estimator. In contrast to the classical Good-Turing estimator, the new formulation needs neither expectations approximations nor windowing or other smoothing techniques. It also contains the well known discounting estimators as special cases. Performance is evaluated both in terms of perplexity and word error rate in an N-best rescoring task. Also comparison to other classical estimators is performed. In all cases our approach performs significantly better than classical estimators. <![CDATA[A method solving an inverse problem with unknown parameters from two sets of relative measurements]]> This work deals with an ill-posed inverse problem in which a distribution function, f(x), is estimated from two independent sets of non-negative relative measurements. Each measurement set is modeled through a Fredholm equation of the first kind, with unknown parameters in its kernel. While the first measurement model only includes a scalar unknown parameter, p0, the second model contains a vector of unknown parameters, p. The proposed method consists of the following steps: (i) to obtain a first estimate of f(x) and p0 from the first measurement; (ii) to estimate the vector p from the second measurement and the previous estimate of f(x); and (iii) to estimate an improved f(x) by simultaneously using both measurements and the estimated parameters in a unique combined problem. The proposed algorithm is evaluated through a numerical example for simultaneously estimating the particle size distribution and the refractive index of a polymer latex, from combined measurements of elastic light scattering and turbidity. <![CDATA[New Steiglitz-McBride adaptive lattice notch filters]]> Two novel adaptive notch filters are presented. The updating algorithms are based on the Steiglitz-McBride error criterion minimization and the basic realizations of the notch filters are all-pass based lattice filters. The proposed realizations represent an extension of a previous ad-hoc scheme for adaptive notch filtering and avoid finding the roots of a high order polynomial to obtain the unknown frequencies of interest. Since the structure is based on the lattice realization, suitable properties with finite length precision realizations can be expected. Computer simulations are included to verify the adaptive filter performance when compared with alternative realizations. <![CDATA[An NIIR structure using HL CPWL functions]]> In this paper we present a nonlinear infinite impulse response (NIIR) model structure for black-box identification of nonlinear dynamic systems. The proposed model structure allows the implementation of an identification algorithm in which the degrees of freedom of the Nonlinear Output Error (NOE) model can be easily increased or decreased during the identification process. This property is very attractive to find the appropriate NIIR model, avoiding overfitting. This is done using High Level Canonical Piecewise Linear (HL CPWL) functions with an increasing (decreasing) grid division. Therefore, the algorithm may start using a linear estimation of the model. The parameters of the HL CPWL functions are updated using a simple algorithm based on a modified steepest descent method with an independently adaptive learning rate.