Technological University of the Mixteca

About: Technological University of the Mixteca is a education organization based out in Ciudad de Huajuapan de León, Mexico. It is known for research contribution in the topics: Varistor & Active disturbance rejection control. The organization has 545 authors who have published 627 publications receiving 4292 citations.

Vlba determination of the distance to nearby star-forming regions. i. the distance to t tauri with 0.4% accuracy

Abstract: In this article, we present the results of a series of 12 3.6 cm radio continuum observations of T Tau Sb, one of the companions of the famous young stellar object T Tauri. The data were collected roughly every 2 months between 2003 September and 2005 July with the Very Long Baseline Array (VLBA). Thanks to the remarkably accurate astrometry delivered by the VLBA, the absolute position of T Tau Sb could be measured with a precision typically better than about 100 μas at each of the 12 observed epochs. The trajectory of T Tau Sb on the plane of the sky could therefore be traced very precisely and was modeled as the superposition of the trigonometric parallax of the source and an accelerated proper motion. The best fit yields a distance to T Tau Sb of 147.6 ± 0.6 pc. The observed positions of T Tau Sb are in good agreement with recent infrared measurements, but they seem to favor a somewhat longer orbital period than that recently reported by Duchene and coworkers for the T Tau Sa/T Tau Sb system.

Linear and nonlinear kinetic and isotherm adsorption models for arsenic removal by manganese ferrite nanoparticles

Abstract: In the present work, we analyzed the linear and nonlinear model suitabilities for adsorption data from aqueous As(III) removal by manganese ferrite nanoparticles (NPs). Hence, As(III) adsorption onto ferrite NPs was formerly analyzed by the intraparticle diffusion model (IPD). Then, adsorption kinetics was described by the pseudo-first-order (PFO), pseudo-second-order (PSO), and Elovich models, while equilibrium adsorption was fitted to the Freundlich and Langmuir isotherms. Linear and nonlinear kinetic and isotherm models were solved and compared. The nonlinear data fitting was applied through the lsqcurvefit user-defined function (Matlab ver. 7.10.0). The initial adsorption rate was influenced by intraparticle diffusion and surface or film diffusion from the arsenic bulk solution to ferrite NPs, according to the IPD model. Adsorption kinetics of As(III) on manganese ferrite NPs was better described by the PSO model, followed by the Elovich model and then the PFO model. Equilibrium adsorption data were only worthily described by the Freundlich isotherm model. While the PSO, Elovich and Freundlich linear models showed even better fit than the nonlinear models, determinant bias was depicted for the PFO and Langmuir linear models. Thus, to use nonlinear adsorption models is highly advisable, having the Matlab lsqcurvefit function been proven very useful to face such task.

Food Safety through Natural Antimicrobials

Abstract: Microbial pathogens are the cause of many foodborne diseases after the ingestion of contaminated food. Several preservation methods have been developed to assure microbial food safety, as well as nutritional values and sensory characteristics of food. However, the demand for natural antimicrobial agents is increasing due to consumers’ concern on health issues. Moreover, the use of antibiotics is leading to multidrug resistant microorganisms reinforcing the focus of researchers and the food industry on natural antimicrobials. Natural antimicrobial compounds from plants, animals, bacteria, viruses, algae and mushrooms are covered. Finally, new perspectives from researchers in the field and the interest of the food industry in innovations are reviewed. These new approaches should be useful for controlling foodborne bacterial pathogens; furthermore, the shelf-life of food would be extended.

Robust Backstepping Tracking Controller for Low-Speed PMSM Positioning System: Design, Analysis, and Implementation

Abstract: This paper is concerned with the design and implementation of a robust position backstepping tracking controller for a permanent magnet synchronous motor (PMSM). The information on the angular position and velocity, provided by a classical resolver-to-digital converter, additionally employs a phase lock loop (PLL) circuit. A backstepping control law is designed from the input–output linearization of the PMSM model, written in $d$ – $q$ coordinates. This controller is adapted via the online estimation of the unknown load torque and friction effects. A linear extended state observer is devised for this purpose, thus ensuring high closed-loop performance of the motor trajectory tracking task. An input-state stability analysis of the entire system is also provided. Cosimulation via the MATLAB/Simulink-PSIM package, including realistic measurement disturbances, is used to investigate the stability and accuracy of the proposed control algorithm. Experimental results are provided.

Algebraic Identification and Estimation Methods in Feedback Control Systems

Abstract: Algebraic Identification and Estimation Methods in Feedback Control Systems presents a model-based algebraic approach to online parameter and state estimation in uncertain dynamic feedback control systems. This approach evades the mathematical intricacies of the traditional stochastic approach, proposing a direct model-based scheme with several easy-to-implement computational advantages. The approach can be used with continuous and discrete, linear and nonlinear, mono-variable and multi-variable systems. The estimators based on this approach are not of asymptotic nature, and do not require any statistical knowledge of the corrupting noises to achieve good performance in a noisy environment. These estimators are fast, robust to structured perturbations, and easy to combine with classical or sophisticated control laws.This book uses module theory, differential algebra, and operational calculus in an easy-to-understand manner and also details how to apply these in the context of feedback control systems. A wide variety of examples, including mechanical systems, power converters, electric motors, and chaotic systems, are also included to illustrate the algebraic methodology.Key features:Presents a radically new approach to online parameter and state estimation.Enables the reader to master the use and understand the consequences of the highly theoretical differential algebraic viewpoint in control systems theory.Includes examples in a variety of physical applications with experimental results.Covers the latest developments and applications.Algebraic Identification and Estimation Methods in Feedback Control Systems is a comprehensive reference for researchers and practitioners working in the area of automatic control, and is also a useful source of information for graduate and undergraduate students.