Efren Gorrostieta-Hurtado

Modeling Key Parameters for Greenhouse Using Fuzzy Clustering Techniques

The clustering techniques are usually used in classification and pattern recognition. Moreover, fuzzy logic is used for system modeling when the information is scarce, inaccurate or its behavior is described using a complex mathematical model. As example of this type of system, a greenhouse is considered, where the variables are: in-house and out-house temperature, humidity for both inside and outside the greenhouse and wind direction. These variables show a dynamic and non-linear behavior; being the in-house temperature and internal humidity the variables of concern for the greenhouse control and modeling. In this project, the development and implementation of three clustering algorithms, being fuzzy K-means, Fuzzy C-means and fuzzy clustering subtractive, is presented. This project is used as the foundation for the design of fuzzy systems and its application in temperature and humidity modeling of a greenhouse used as a laboratory of biotronics at the Universidad Autonoma de Queretaro.

Comparison between Fuzzy C-means clustering and Fuzzy Clustering Subtractive in urban air pollution

Clustering is generally associated with classification problem. In this contribution, the implementation of cluster estimation method as a basis of a fuzzy model identification algorithm has been developed. A comparison between two different clustering techniques is presented, Fuzzy C-means clustering and Fuzzy Clustering Subtractive. Also, an application in modeling the relationship between temperature, humidity and PM10 concentration in urban air pollution in Liverpool at northwest of England is presented.

Performance assessment of fuzzy clustering models applied to urban airborne pollution

An application in modeling a non-lineal system between temperature, humidity and urban airborne air pollution is presented. In this contribution, the implementation of cluster estimation method as a basis of a fuzzy model identification algorithm has been developed. Fuzzy clustering allowed partitioning this complex non-linear system into many linear sub-systems. Finally, comparison of the performance between two different clustering techniques for this particular case study is presented: Fuzzy C-means Clustering and Fuzzy Subtractive Clustering.

A comparison between local and global phase unwrapping algorithms in a modified Fourier Transform Profilometry Method

This work present a modified Fourier Transform Profilometry method, in particular, the development of local and global phase unwrapping algorithms has been considered, because this is one of the major challenges when this method is applied. The basic idea is to project a sinusoidal fringe pattern with a known spatial frequency on the object to digitize, and then a vision system captures and processes the image to obtain the objects depth information. First, the fringe pattern is projected on a reference plane then an image is acquired, later the object to digitize is placed in front of the reference plane and then another image is acquired. The fringe pattern is distorted due to the objects irregular shape. One of the main difficulties to face is the high frequency content in the unwrapping process. This effect can be minimized by knowing the spatial frequency and its multiples. Here, we propose to implement global and local phase unwrapping algorithms to overcome the high frequency problems. These algorithms are part of the modified Fourier Transform Profilometry Method (FTP), where the resulting phase difference of the acquired and processed images have the information of the objects depth. Some tests with computer generated and real objects with different geometries are carried out to verify the proposed methodology, considering the factors that mostly affect the method.

A Profilometric Approach for 3D Reconstruction Using Fourier and Wavelet Transforms

In this research, an improved method for three-dimensional shape measurement by fringe projection is presented. The use of Fourier and Wavelet transform based analysis to extract the 3D information from the objects is proposed. The method requires a single image which contains a sinusoidal white light fringe pattern projected on it. This fringe pattern has a known spatial frequency and this information is used to avoid the discontinuities in the fringes with high frequency. Several computer simulations and experiments have been carried out to verify the analysis. The comparison between numerical simulations and experiments has proved the validity of this proposed method.

A 3D Sensor Based on a Profilometrical Approach

An improved method which considers the use of Fourier and wavelet transform based analysis to infer and extract 3D information from an object by fringe projection on it is presented. This method requires a single image which contains a sinusoidal white light fringe pattern projected on it, and this pattern has a known spatial frequency and its information is used to avoid any discontinuities in the fringes with high frequency. Several computer simulations and experiments have been carried out to verify the analysis. The comparison between numerical simulations and experiments has proved the validity of this proposed method.

Evaluating trends of airborne contaminants by using support vector regression techniques

Monitoring, modeling and forecasting of air quality parameters are important topics in environmental and health research due to their impact caused by exposing to air pollutants in urban environments. The aim of this article is to show that forecast of daily airborne pollution using support vector machines (SVM) is feasible in regression mode. Results are presented using data measurements of Particulate Matter of aerodynamical size on the order of 10 and 2.5 micrograms (PMx) in London-Bloomsbury at south England.

Fuzzy logic hardware implementation for pneumatic control of one DOF pneumatic robot

The pneumatic actuators can be a useful way to control the position of a manipulator robot, instead of an electrical actuator. The major problem with pneumatic actuators is the compressibility of the air, due to the fact that the mathematical model is a system formed by a set of highly non-linear equations then a simple PID control is not enough to control the robot position, and fuzzy logic is a good option. This work is focused on the hardware implementation of Fuzzy logic algorithm into FPGA system. This paper also presents a methodology to implement a pneumatic control using fuzzy logic, into a FPGA device, which is the main contribution of this work. The air flow is controlled with a pulse width modulation, applied to the pneumatic electro- valve, with 25 ms of period.

Simulation Methodology for Mechatronic Applications using Multilanguage Techniques

Abstract This paper presents a simulation methodology proposal, applying a multilanguage technique to simulate a mechatronic system. Firstly, a way to interact between two programming languages is presented, by taking advantage of each language to facilitate the development of a complex simulation tool. Later, the mechanical structure is obtained in VRML format. Next, special software is used to compute the mathematical model for kinematics and dynamic behavior. The results are showed by graphical simulation with Graphic Libraries support. Finally, the methodology is applied to flexible manipulator with one degree of freedom as study case, and the graphical simulation is presented.

Simulation of a two DOF pneumatic manipulator robot using control based on back propagation neural network

Although pneumatic actuators have a good power-weight ratio, there is a reduced number of works that consider them to be applied in manipulator robots, mainly because they present difficulties to be controlled, and nonlinearities that make them complicated to obtain a mathematical model which describes their behavior in specific conditions. Control techniques can be implemented in this kind of actuators, and they can be complemented with path tracking to follow trajectories established by the user. This paper proposes software implementation of a back propagation artificial neural network to control a two DOF pneumatic manipulator and compares this method against PID control decreasing processing time and oscillations by self tuning parameters of the controller. Path tracking is realized using an algorithm of cubic splines interpoation and the movement of the pneumatic robot is presented in a graphic simulator developed in C++ using OpenGL libraries.