A new approach to fuzzy estimation of Takagi-Sugeno model and its applications to optimal control for nonlinear systems

An efficient approach is presented to improve the local and global approximation and modelling capability of Takagi-Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy. The main problem is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the use of the T-S method because this type of membership function has been widely used during the last two decades in the stability, controller design and are popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S method with optimized performance in approximating nonlinear functions. A simple approach with few computational effort, based on the well known parameters' weighting method is suggested for tuning T-S parameters to improve the choice of the performance index and minimize it. A global fuzzy controller (FC) based Linear Quadratic Regulator (LQR) is proposed in order to show the effectiveness of the estimation method developed here in control applications. Illustrative examples of an inverted pendulum and Van der Pol system are chosen to evaluate the robustness and remarkable performance of the proposed method and the high accuracy obtained in approximating nonlinear and unstable systems locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity and generality of the algorithm.

Gear dynamics monitoring using discrete wavelet transformation and multi-layer perceptron neural networks

This paper presents a multi-stage algorithm for the dynamic condition monitoring of a gear. The algorithm provides information referred to the gear status (fault or normal condition) and estimates the mesh stiffness per shaft revolution in case that any abnormality is detected. In the first stage, the analysis of coefficients generated through discrete wavelet transformation (DWT) is proposed as a fault detection and localization tool. The second stage consists in establishing the mesh stiffness reduction associated with local failures by applying a supervised learning mode and coupled with analytical models. To do this, a multi-layer perceptron neural network has been configured using as input features statistical parameters sensitive to torsional stiffness decrease and derived from wavelet transforms of the response signal. The proposed method is applied to the gear condition monitoring and results show that it can update the mesh dynamic properties of the gear on line.

Gestión de costos medioambientales en la industria petroquímica

Se analiza la gestión de costos medioambientales que lleva a cabo la industria petroquímica del estado Zulia - Venezuela. El diseño de la investigación es no experimental, de tipo descriptiva - analítica y transeccional; se utilizaron como técnicas de recolección de información, la revisión documental y la entrevista estructurada a través de un cuestionario; la población estuvo constituida por las ocho empresas del sector petroquímico que operan en el estado Zulia, realizándose un censo de la misma. Los resultados muestran que existen debilidades en la gestión de costos realizada por las empresas petroquímicas, ya que no clasifican sus costos medioambientales adecuadamente, no los distribuyen a sus costos de producción, ni los operan con criterios de ecoeficiencia, por lo que se recomienda incorporar la categoría de costos de evaluación o detección a la clasificación de costos realizada actualmente; distribuir los costos medioambientales a los productos tomando una base funcional de aplicación y determinar indicadores de costos y rentabilidad medioambiental, que permitan evaluar el comportamiento de estos costos y realizar comparaciones entre diferentes períodos y con otras empresas del sector.

Variable structure control with chattering elimination and guaranteed stability for a generalized T-S model

In this paper, a fuzzy based Variable Structure Control (VSC) with guaranteed stability is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. The main contribution of this work is that, firstly, new functions for chattering reduction and error convergence without sacrificing invariant properties are proposed, which is considered the main drawback of the VSC control. Secondly, the global stability of the controlled system is guaranteed.The well known weighting parameters approach, is used in this paper to optimize local and global approximation and modeling capability of T-S fuzzy model.A one link robot is chosen as a nonlinear unstable system to evaluate the robustness, effectiveness and remarkable performance of optimization approach and the high accuracy obtained in approximating nonlinear systems in comparison with the original T-S model. Simulation results indicate the potential and generality of the algorithm. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved with the proposed FLC-VSC controller. The effectiveness of the proposed controller is proven in front of disturbances and noise effects.

Discussion of "Design Footing Area with Biaxial Bending" by Ramon Jarquio and Victor Jarquio (October, 1983)

The authors present a very interesting criterion for choosing a rectangular foundation.The writers should like to point out that the obtention of minimum area can be reduced to the problem of finding the minimum of x*+y*, subjected to the condition x*.y*=k2 whose solution is evidently x*=y*=k