Oscar Fernando Avilés Sánchez

Review of Connector Docking Systems for Modular Robotic Systems

There are robots in the field of modular robotics with capabilities of self – reconfiguration. These have the ability to change their own shape at will, reordering connections with the purpose of adapting to new circumstances, new tasks or recovering from damages. In recent years, new systems have been developed to allow physically binding modules. The aim of this paper is to illustrate in a clear way, the different connection systems and the solutions that exist for coupling them in modular robots. Therefore this document is composed by the system used, important features, schemes to understand how they work and examples of robots where these systems have been implemented. As a conclusion, a number of features that should be taken into account when choosing a coupling system or designing a new one are shown.

Design and Implementation of a Neural Network Applied to the Maximum Power Point Tracking of a Solar Panel

This paper shows the design and implementation of a neural network using back propagation method in order to perform the tracking of the maximum power point of a solar panel; this can be achieved by the use of the predictive ability of the network which uses light sensors to perform angular movement of the panel to find the optimum position. Tests were performed both in artificial and real environments; the network tracking sensitivity was tested in the artificial environment and it gave a result of less than 8 degrees of error, on the other hand in terms of voltage an improvement of more than 25% was found on the tracking configuration against an static configuration. As for the real environment testing, the tracking achieved to find the value of maximum power with a difference smaller than 4% of the maximum power measurement obtained.

Adaptive Control for Solar Photovoltaic Tracking System

This paper describes the behavior of adaptive control using the MIT rule for a polar aligned single axis tracking system, it´s for increase the efficiency of solar energy capturing compared to a polar fixed system, where the response of system is analyzed by simulation in Simulink – MATLAB® software. The data input for estimate the energy in the photovoltaic panels is the radiation data, that is obtained by weather station of the CAR (regional autonomous corporation) situated in the zone of study. The objective of the integration between the photovoltaic panel and the mechanics tracking system is to keep the perpendicular sunlight during the day. The MIT adaptive control tries to reduce possible errors, such a sun position data deviations, friction and environmental changes in the conventional solar tracking. This control was designed according to a typical polar aligned single axis tracker.

Design of Sliding Mode Based Differential Flatness Control of Leg-Wheel Hybrid Robot

The sliding mode based differential flatness control is used to stabilize the error dynamics in view of unmodeled dynamics employing position, velocity and acceleration as reference values but feeding back to system only the position and velocity measurements. This controller is able to plan trajectories of control gains within the proposed scheme of the controller. By above this paper describes a sliding mode based differential flatness control to a leg-wheel hybrid robot, in order to design a robotic prototype with the ability to move an uneven ground. To prove the controller working a simulation in Matlab-Simulink using Simmechanics is made. The result of this work shows a controller that is able to follow the reference trajectories without overshoots and small chattering.

Linear Control for Full Bridge Phase PWM Rectifier

Rectifiers are widely use in areas of industry and commerce to implement equipment which require to be powered by alternating current (AC) source, so that uncontrolled rectification requires an operational requirement study because they only properly works if the rectifier calculated boundary conditions are ideal and invariant. Therefore the implementation of control strategies should be take into account to generate the desired signal performance in the rectifier. This document shows the implementation of different control techniques on the behavior the sinusoidal current in a single-phase rectifier width modulated pulse and resistive load. Consequently, in this work the development of several control strategies are presented, for behavior analysis of signals in a rectifier with width pulse modulation and resistive load. Additionally, a comparison between the developed controllers is performed in order to get the best behavior available for this applications.

Hybrid Force-Position Control Three Fingers End Effector

This paper describes the implementation of a hybrid controller to an end effector of threefingers, each finger with two degrees of freedom (2 DOF). Since the mobility of each phalanx showsthe workspace by finger. Modeling is presented which includes the kinematics and dynamics offector and implementation of force-position hybrid controller. Simulations are presented to validatethe behavior of the finger and the controller in Matlab Simulink.

Intelligent Traffic Controller with Priority for Emergency Vehicles

This paper describes the development of a traffic controller using fuzzy logic, combined with the analysis of video sequences through machine vision techniques. The controller is able to automatically manage the traffic flow in a set of intersections, giving priority to the traffic lights of roads where there are emergency vehicles waiting. The system uses a classification algorithm, which is trained in order to detect any vehicle the scene and an image processing algorithm that identifies emergency vehicles within the previously detected vehicles. Using the information of video sequences acquired with CCD cameras installed on the intersections, the system choose the sequence of actions that improves the traffic flow, so as to increase the mobility in the road where the emergency vehicle is detected. Results show that the system is able to detect vehicles in real time. Also, the system adapts in an efficient and fast way to the changes in traffic flow in order to establish a priority road for emergency vehicles.This paper describes the development of a traffic controller using fuzzy logic, combined with the analysis of video sequences through machine vision techniques. The controller is able to automatically manage the traffic flow in a set of intersections, giving priority to the traffic lights of roads where there are emergency vehicles waiting. The system uses a classification algorithm, which is trained in order to detect any vehicle the scene and an image processing algorithm that identifies emergency vehicles within the previously detected vehicles. Using the information of video sequences acquired with CCD cameras installed on the intersections, the system choose the sequence of actions that improves the traffic flow, so as to increase the mobility in the road where the emergency vehicle is detected. Results show that the system is able to detect vehicles in real time. Also, the system adapts in an efficient and fast way to the changes in traffic flow in order to establish a priority road for emergency vehicles.