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Gustavo A. Madero, Mexico
Gustavo A. Madero, Mexico
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Aguilar-Ibanez C.,CIC IPN | Suarez-Castanon M.S.,Escuela Superior de Computo IPN
International Journal of Control | Year: 2010

A nonlinear controller for the stabilisation of the Furuta pendulum is presented. The control strategy is based on a partial feedback linearisation. In a first stage only the actuated coordinate of the Furuta pendulum is linearised. Then, the stabilising feedback controller is obtained by applying the Lyapunov direct method. That is, using this method we prove local asymptotic stability and demonstrate that the closed-loop system has a large region of attraction. The stability analysis is carried out by means of LaSalle's invariance principle. To assess the controller effectiveness, the results of the corresponding numerical simulations are presented. © 2010 Taylor & Francis.


Pena-Ayala A.,WOLNM | Pena-Ayala A.,Osaka University | Sossa-Azuela H.,CIC IPN | Cervantes-Perez F.,National Autonomous University of Mexico
Expert Systems with Applications | Year: 2012

In this article we explore the paradigm of student-centered education. The aim is to enhance the learning of students by the self-adaptation of a Web-based educational system (WBES). The adaptive system's behavior is achieved as a result of the decisions made by a student model (SM). The decision reveals the lecture option most suitable to teach a concept according to the student's profile. Thus, the lecture content is authored from different view points (e.g. learning theory, type of media, complexity level, and user-system interaction degree). The purpose is to tailor several educational options to teach a given concept. Thereby, the SM elicits psychological attributes of the student to describe subjective traits, such as: cognitive, personality, and learning preferences. It also depicts pedagogical properties of the available lecture's options. Moreover, the SM dynamically builds a cognitive map (CM) to set fuzzy-causal relationships among the lecture's option properties and the student's attributes. Based on a fuzzy-causal engine, the SM predicts the bias that a lecture's option exerts on the student's apprenticeship. The conceptual, theoretical, and formal grounds of the approach were tested by a computer implementation of the SM and an experiment. As a result of a field trial, we found that: the average learning acquired by an experimental group of volunteers that used this approach was 17% higher than the average apprenticeship of another equivalent control group, whose lectures were randomly chosen. Thus we conclude that: learning is better stimulated when the delivered lectures account a student's profile than when they ignore it. © 2011 Elsevier Ltd. All rights reserved.


Jimenez S.,National University of Colombia | Gonzalez F.A.,National University of Colombia | Gelbukh A.,CIC IPN
Information Sciences | Year: 2016

The soft cardinality function generalizes the concept of counting measure of the classic cardinality of sets. This function provides an intuitive measure of the amount of elements in a collection (i.e. a set or a bag) exploiting the similarities among them. Although soft cardinality was first proposed in an ad-hoc way, it has been successfully used in various tasks in the field of natural language processing. In this paper, a formal definition of soft cardinality is proposed together with an analysis of its boundaries, monotonicity property and a method for constructing similarity functions. Additionally, an empirical evaluation of the model was carried out using synthetic data. © 2016 Elsevier Inc.


Jimenez S.,National University of Colombia | Gonzalez F.,National University of Colombia | Gelbukh A.,CIC IPN
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

The classical set theory provides a method for comparing objects using cardinality and intersection, in combination with well-known resemblance coefficients such as Dice, Jaccard, and cosine. However, set operations are intrinsically crisp: they do not take into account similarities between elements. We propose a new general-purpose method for comparison of objects using a soft cardinality function that show that the soft cardinality method is superior via an auxiliary affinity (similarity) measure. Our experiments with 12 text matching datasets suggest that the soft cardinality method is superior to known approximate string comparison methods in text comparison task. © 2010 Springer-Verlag.


Pena-Ayala A.,National Polytechnic Institute of Mexico | Sossa-Azuela J.H.,CIC IPN
Intelligent Systems Reference Library | Year: 2014

In this chapter we outline a decisions-making approach (DMA) that is based on the representation and simulation of causal phenomena. It applies an extension of the traditional Fuzzy Cognitive Maps called Rules-based Fuzzy Cognitive Maps (RBFCM). This version depicts the qualitative flavor of the object to be modeled and is grounded on the well-sounded fuzzy logic. As a result of a case study in the educational field, we found empirical evidence of the RBFCM usefulness. Our DMA offers decision-making services to the sequencing module of an intelligent and adaptive web-based educational system (IAWBES). According to the studentcentered education paradigm, an IAWBES elicits learners’ traits to adapt lectures to enhance their apprenticeship. This RBFCM based DMA models the teachinglearning scenery, simulates the bias exerted by authored lectures on the student’s learning, and picks the lecture option that offers the highest achievement. The results reveal that the experimental group reached higher learning than the control group. © Springer-Verlag Berlin Heidelberg 2014.


Aguilar-Ibanez C.,CIC IPN | Garrido-Moctezuma R.,CINVESTAV | Davila J.,National Polytechnic Institute of Mexico
ISA Transactions | Year: 2012

This work proposes a solution for the output feedback trajectory-tracking problem in the case of an uncertain DC servomechanism system. The system consists of a pendulum actuated by a DC motor and subject to a time-varying bounded disturbance. The control law consists of a Proportional Derivative controller and an uncertain estimator that allows compensating the effects of the unknown bounded perturbation. Because the motor velocity state is not available from measurements, a second-order sliding-mode observer permits the estimation of this variable in finite time. This last feature allows applying the Separation Principle. The convergence analysis is carried out by means of the Lyapunov method. Results obtained from numerical simulations and experiments in a laboratory prototype show the performance of the closed loop system. © 2012 ISA.


Aguilar-Ibanez C.,CIC IPN | Suarez-Castanon M.S.,Escuela Superior de Computo Del IPN | Rosas-Soriano L.I.,CIC IPN
International Journal of Robust and Nonlinear Control | Year: 2011

We present a simple control scheme for changing the position of a microscopic particle immersed in a viscous medium and trapped by optical tweezers. We derive a simple feedback controller under the consideration that the particle mass is so small that it can be discarded from the motion equations. This approximation is well justified in practice, since the inertial force produced by the motion of a micron-scaled trapped particle is completely dominated by the medium viscous drag force. Finally, we formally prove that the obtained controller is able to globally asymptotically stabilize the system when the particle mass is considered, if some suitable values of some control parameter are used. The stability analysis of the controlled system was carried out by using the standard Lyapunov stability theory. Also, by means of numerical simulations, we show that the obtained closed-loop system is robust when random thermal noise is presented. © 2010 John Wiley & Sons, Ltd.


Sossa H.,CIC IPN | Guevara E.,CIC IPN
Neurocomputing | Year: 2014

This paper introduces an efficient training algorithm for a dendrite morphological neural network (DMNN). Given p classes of patterns, Ck, k=1, 2, ..., p, the algorithm selects the patterns of all the classes and opens a hyper-cube HCn (with n dimensions) with a size such that all the class elements remain inside HCn. The size of HCn can be chosen such that the border elements remain in some of the faces of HCn, or can be chosen for a bigger size. This last selection allows the trained DMNN to be a very efficient classification machine in the presence of noise at the moment of testing, as we will see later. In a second step, the algorithm divides the HCn into 2n smaller hyper-cubes and verifies if each hyper-cube encloses patterns for only one class. If this is the case, the learning process is stopped and the DMNN is designed. If at least one hyper-cube HCn encloses patterns of more than one class, then HCn is divided into 2n smaller hyper-cubes. The verification process is iteratively repeated onto each smaller hyper-cube until the stopping criterion is satisfied. At this moment the DMNN is designed. The algorithm was tested for benchmark problems and compare its performance against some reported algorithms, showing its superiority. © 2013 Elsevier B.V.


Aguilar-Ibanez C.,CIC IPN | Martinez-Garcia J.C.,CINVESTAV | Soria-Lopez A.,CINVESTAV
Proceedings of the IEEE Conference on Decision and Control | Year: 2011

We are concerned in this paper by bounded control of nonlinear underactuated dynamical systems. We focus our exposition on a feedback-based stabilization bounded control action shaped by saturation functions. A simple stabilizing controller for the well-known cart-pendulum system is then designed in this paper. Our control strategy describes in lumped linear time-invariant terms the concerned underactuated nonlinear system as a cascade nonlinear dynamical system consisted of a simple chain of four integrators with a high-order smooth nonlinear perturbation, and assumes initialization of the resulting underactuated system in the upperhalf plane. Our proposed feedback-based regulation design procedure involves the simultaneous combination of two control actions: one bounded linear and one bounded quasilinear. Control boundedness is provided in both involved control actions by specific saturation functions. The first bounded control action brings the non-actuated coordinate near to the upright position and keep it inside of a well-characterized small vicinity, whereas the second bounded control action asymptotically brings the whole state of the dynamical system to the origin. The necessary closed-loop stability analysis uses standard linear stability arguments as well as the traditional well-known Lyapunov method and the LaSalle's theorem. Our proposed control law ensures global stability of the closed-loop system in the upper half plane, while avoiding the necessity of solving either partial differential equations, nonlinear differential equations or fixed-point controllers. We illustrate the effectiveness of the proposed control strategy via numerical simulations. © 2011 IEEE.


Aguilar-Ibanez C.,CIC IPN | Suarez-Castanon M.S.,ESCOM IPN | Rubio J.D.J.,SEPI ESIME Azcapotzalco
Mathematical Problems in Engineering | Year: 2012

A novel inverse Lyapunov approach in conjunction with the energy shaping technique is applied to derive a stabilizing controller for the ball on the beam system. The proposed strategy consists of shaping a candidate Lyapunov function as if it were an inverse stability problem. To this purpose, we fix a suitable dissipation function of the unknown energy function, with the property that the selected dissipation divides the corresponding time derivative of the candidate Lyapunov function. Afterwards, the stabilizing controller is directly obtained from the already shaped Lyapunov function. The stability analysis of the closed-loop system is carried out by using the invariance theorem of LaSalle. Simulation results to test the effectiveness of the obtained controller are presented. Copyright © 2012 Carlos Aguilar-Ibaez et al.

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