Leocundo Aguilar

Intelligent control of a stepping motor drive using a hybrid neuro-fuzzy ANFIS approach

Abstract Stepping motors are widely used in robotics and in the numerical control of machine tools where they have to perform high-precision positioning operations. However, the variations of the mechanical configuration of the drive, which are common to these two applications, can lead to a loss of synchronism for high stepping rates. Moreover, the classical open-loop speed control is weak and a closed-loop control becomes necessary. In this paper, fuzzy logic is applied to control the speed of a stepping motor drive with feedback. A neuro-fuzzy hybrid approach is used to design the fuzzy rule base of the intelligent system for control. In particular, we used the adaptive neuro-fuzzy inference system (ANFIS) methodology to build a Sugeno fuzzy model for controlling the stepping motor drive. An advanced test bed is used in order to evaluate the tracking properties and the robustness capacities of the fuzzy logic controller.

Genetic optimization of a Type-2 fuzzy controller for output regulation of a servomechanism with backlash

A genetic-type-2 fuzzy logic controller (FLC) is proposed to achieve the output regulation of a servomechanism with backlash. The problem is the design of a type-2 FLC, which will be optimized by a genetic algorithm (GA) to obtain the closed-loop system in which the load of the driver is regulated to a desired position. The provided servomotor position is the only measurement available for feedback. Simulations results illustrate the effectiveness of the optimized closed-loop system.

Teaching mobile and wireless information systems development in engineering courses

MADEE (Mobile Application Development and Execution Environment) is a platform that supports the development of small and middle size mobile and wireless information systems for handheld devices. MADEE allows a student to develop applications faster and easier than using conventional development tools. This study presents the results and experience obtained using MADEE to support the introduction of mobile and wireless information systems development concepts in the context of computer engineering courses.

An experimental wireless sensor network applied in engineering courses

Wireless sensor networks (WSNs) are an emerging technology based on the progress of electrical and mechanical engineering, as well as computer science in the last decade. This paper presents our experiences in designing and developing a WSN using commercial‐off‐the‐shelf components and assembled in‐house. This WSN is used as a support tool for teaching in undergraduate engineering programs in Electronic and Computing, providing students a hands‐on experience with emphasis on embedded software design.

Developing programming tools to reach a deeper understanding of advanced programming concepts

This article describes the experience and results obtained teaching non‐common Java features, in advanced undergraduate object‐oriented programming courses. The teaching approach proposed helps students to reach a deeper level of programming expertise, while accomplishing specific assignments that integrate a class framework that supports implementation of medium size client–server applications.

Estimating Indoor Zone-Level Location Using Wi-Fi RSSI Fingerprinting Based on Fuzzy Inference System

Recent advances in communication and mobile technology have becoming the Wireless Local Area Networks using Wi-Fi more ubiquitous. These networks are providing a potential infrastructure that enable the location of users wearing wireless devices indoor, where GPS (Global Position System) signal is weak or is not available. Trilateration and Fingerprinting are the two conventional and general methods used for calculating location using Wi-Fi RSSI (received signal strength indicator) data. This work presents an alternative method to people indoor localization using the Wi-Fi RSSI Fingerprinting based on Fuzzy Inference Systems estimator in a wearable wristband. Wi-Fi Fingerprinting creates a radio map of a given area based on the RSSI data from several access points (APs) and generates a set of RSSI data for a given zone location. Then the Fuzzy Inference System is trained with that set of data and upon the system is trained, live RSSI values are introduced to the Fuzzy Inference System to generate an estimation of the user zone location.

Experiences using PSP and XP to support teaching in undergraduate programming courses

Computer programming has a technological part and a creative part; it involves specific technical aspects of programming languages and creative aspects to find the best solutions for different problem domains. The programming learning process encompasses a group of different teacher–student techniques that are put into practice. These techniques have the object of learning a programming language to solve real problems; in this learning process we must include good software development practices of analysis and design so the novice programmer disciplines himself into developing quality software. To improve the learning programming process we use techniques and methods of software development adapting them to the context of courses in programs of the curricula. There are different methods to help us develop quality software; this article is a case study of using PSP (Personal Software Process) method and XP (eXtreme Programming) techniques on curriculas first programming course for engineering students, as support of the learning process of a programming language, and acquiring good software development habits.

End-to-End Message Exchange in a Deployable Marine Environment Hierarchical Wireless Sensor Network

We present a pragmatic view of different approaches used to guarantee data delivery in a deployable marine habitat monitoring system, composed of a two-tier dual frequency (2.4 GHz/900 MHz) hierarchical wireless sensor network (WSN). We cover end-to-end application layer aspects. At the lower tier, we preconfigured endpoint (EP) transceivers for automatic data acquisition and wireless transfer using their native Application Program Interface (API) framework. These endpoints communicate with a more powerful intermediate cluster-head (CLH) system. At the upper tier, we deployed a modified low level 8-bit “Lighter” version of the well-known web application protocol called JavaScript Object Notation (JSON, or in our case LJSON) for back and forth CLH to BS validated message exchange. These LJSON messages are converted by the BS to 16-bit JSON and vice versa, for remote Internet interaction. And finally, the BS software establishes Internet Protocol (IP) client socket connections with a remote custom JSON service, in charge of marine habitat sensor data reception, verification, and nonvolatile database storage.

A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals

The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi–Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information.

A Java Compatible Virtual Machine as an Embedded Middleware for Wireless Sensor Networks

Programming Wireless Sensor Networks (WSN) involves learning very different programming paradigms from those commonly used in the development of computer systems. Due to the lack of advantages obtained from the last generation high level programming languages, the growth of WSNs is significantly impeded. Programming WSN nodes requires knowledge of specific hardware which depends on the WSN architecture. A method to provide the benefits of high level languages is to use a hardware abstraction layer. MiniMV is a virtual machine designed to be used in embedded systems and it is capable of executing Java class files (containing a subset java bytecode instructions) created by a Java standard compiler. This work focuses on the implementation of MiniMV in the Tmote Sky platform using the C language and the TinyOS hardware functions as native methods and how MiniMV has been ported to other platform with minimal changes such as LiSANDRA developed by UABC-Tij research group.