RemoteLabs Platform

This paper reports on a first step towards the implementation of a framework for remote experimentation of electric machines ? the RemoteLabs platform. This project was focused on the development of two main modules: the user Web-based and the electric machines interfaces. The Web application provides the user with a front-end and interacts with the back-end ? the user and experiment persistent data. The electric machines interface is implemented as a distributed client server application where the clients, launched by the Web application, interact with the server modules located in platforms physically connected the electric machines drives. Users can register and authenticate, schedule, specify and run experiments and obtain results in the form of CSV, XML and PDF files. These functionalities were successfully tested with real data, but still without including the electric machines. This inclusion is part of another project scheduled to start soon

Monitoring and Control of a Variable Frequency Drive Using PLC and SCADA

Programmable Logic Controller (PLC) and Supervisory Control And Data Acquisition (SCADA) are two new approaches to control a Variable Frequency Drive (VFD) whose output is fed to a three-phase induction motor and driving a conveyor belt. The conveyor belt has three sensors are inputs which senses a passing object and carries out the necessary instructions programmed in ladder logic programming of the PLC through the medium of a personal computer (PC). The SCADA software installed in the PC in turn enables the human operator to control the entire operation away from the plant and just by using the virtual inputs designated on his computer screen. The results have been verified with a validating experiment

Mobile Robotics Platform

Students, particularly those that will be studying in upper-tier Unified Robotics courses at WPI, are in need of a robotics platform that will provide a foundation facilitating laboratory demonstrations and experiments on theoretical concepts in robotics, as well as a basis for robotic projects, allowing a focus on more complicated subjects instead of getting a system up and running first. The main purpose of this project is to design and prototype a modular robotics base that will fulfill the needs of these intended audiences. This base will be modular, allowing mechanical, electronic, and software modifications while maintaining an ease-of-use approach

Wireless industrial intelligent controller for a non-linear system

Modern neural network (NN) based control schemes have surmounted many of the limitations found in the traditional control approaches. Nevertheless, these modern control techniques have only recently been introduced for use on high-specification Programmable Logic Controllers (PLCs) and usually at a very high cost in terms of the required software and hardware. This ‗intelligent‘ control in the sector of industrial automation, specifically on standard PLCs thus remains an area of study that is open to further research and development. The research documented in this thesis examined the effectiveness of linear traditional control schemes such as Proportional Integral Derivative (PID), Lead and Lead-Lag control, in comparison to non-linear NN based control schemes when applied on a strongly non-linear platform. To this end, a mechatronic-type balancing system, namely, the Ball-on-Wheel (BOW) system was designed, constructed and modelled. Thereafter various traditional and intelligent controllers were implemented in order to control the system. The BOW platform may be taken to represent any single-input, single-output (SISO) non-linear system in use in the real world. The system makes use of current industrial technology including a standard PLC as the digital computational platform, a servo drive and wireless access for remote control. The results gathered from the research revealed that NN based control schemes (i.e. Pure NN and NN-PID), although comparatively slower in response, have greater advantages over traditional controllers in that they are able to adapt to external system changes as well as system non-linearity through a process of learning. These controllers also reduce the guess work that is usually involved with the traditional control approaches where cumbersome modelling, linearization or manual tuning is required. Furthermore, the research showed that online-learning adaptive traditional controllers such as the NN-PID controller which maintains the best of both the intelligent and traditional controllers may be implemented easily and with minimum expense on standard PLCs

Web Supervision System of a Freight Elevator

Nowadays, automation and industrial control is an area in which there are innovations ev- ery day in terms of process digitalization, equipment interconnection and human-machine interaction, which results in a constant learning and adaptation to new technologies and methodologies developed. With this comes the responsibility to keep systems robust and prepared for eventual failures, while moving towards an increasing dependence on remote communication between different controllers and different processes. This fact leads to the need to create supervision and monitoring tools capable of detecting and transmitting existing failures, while ensuring that the system continues to operate with the same stability and performance. Therefore, in this work it is proposed the development of a supervisory tool based on industrial automation that has a fault detection component and a human-machine interface in order to incorporate all the essential features of an industrial supervisor. Using industrial programming languages for Programmable Logic Controllers, it was possible to develop an algorithm that is based on inference mechanisms to identify potential faults in the system, which are then transmitted to the user in an interface that can be accessed either locally or remotely via the Web.Nos dias de hoje, a automação e controlo industrial é uma área onde existe todos os dias inovações ao nível da digitalização de processos, da interconexão de equipamentos e na interação Homem-máquina, o que resulta numa constante aprendizagem e adaptação às novas tecnologias e metodologias desenvolvidas. Com isto, vem a responsabilidade de manter os sistemas robustos e preparados para eventuais falhas, ao mesmo tempo que se avança no sentido da cada vez maior dependência da comunicação remota entre diferentes controladores e diferentes processos. Este facto leva a que tenham de ser criadas ferramentas de supervisão e monitorização capazes de detetar e transmitir as falhas existentes, enquanto se garante que o sistema continua em funcionamento garantindo a mesma estabilidade e performance. Assim, neste trabalho é proposto o desenvolvimento de uma ferramenta de supervisão baseada em automação industrial que possua uma componente de deteção de falhas e uma interface Homem-máquina de forma a incorporar todas as funcionalidades essenciais de um supervisor industrial. Recorrendo a linguagens de programação industrial para controladores lógicos programáveis, foi possível desenvolver um algoritmo que se baseia em mecanismos de inferência para identificar potenciais avarias no sistema que são posteriormente transmitidas ao utilizador numa interface que pode ser acedida quer localmente, quer remotamente via Web

Remote laboratories in engineering education: automation system design

This paper deals with the usage of a remote laboratory as a platform for integrating learning into engineering education. It also shows a concept and partial implementation results of a remote laboratory for designing automation systems. Advantages and disadvantages of such a system are elaborated from the didactical, technological and economical point of view and accordingly, their results are presented. Also, an overview of simulation and implementation results is included.. Finally, directions for future work and an on-line application have been outline

A programmable logic controller based laboratory analysis of conventional and intelligent control schemes for non-liner systems

Published ArticleIntelligent Neural Network (NN) based control schemes have surmounted many of the limitations found in the conventional control approaches such as Proportional Integral Derivative (PID) control. Nevertheless, these modern control techniques have only recently been introduced for use on industrial computational platforms such as the Programmable Logic Controller (PLC). Intelligent control on PLCs thus remains an area that is open to further research and development. In this paper, a strongly non-linear mechatronic type system, namely the Ball-on-Wheel balancing system, is developed using a PLC as its control platform. The research details the implementation of an intelligent controller on a standard, medium specification PLC. The results from the intelligent controller are then compared to those produced by a variety of conventional controllers as physical parameters are varied. Finally, the system is presented as a stimulating educational tool that addresses the knowledge gap that exists in industry pertaining to the implementation of these intelligent control algorithms on PLCs

PLC & SCADA based substation automation

lectrical power systems are a technical wonder. Electricity and its accessibility are the\ud greatest engineering achievements of the 20th century. A modern society cannot exist without electricity.\ud Generating stations, transmission lines and distribution systems are the main components of\ud power system. Smaller power systems (called regional grids) are interconnected to form a larger network\ud called national grid, in which power is exchanged between different areas depending upon surplus and\ud deficiency. This requires a knowledge of load flows, which is impossible without meticulous planning and\ud monitoring .Also, the system needs to operate in such a way that the losses and in turn the cost of\ud production are minimum.\ud The major factors that influence the operation of a power system are the changes in load and\ud stability. As is easily understood from the different load curves and load duration curve, the connected\ud load, load varies widely throughout the day. These changes have an impact on the stability of power\ud system. As a severe change in a short span can even lead to loss of synchronism. Stability is also affected\ud by the occurrence of faults, Faults need to be intercepted at an easily stage and corrective measures like\ud isolating the faulty line must be taken.\ud As the power consumption increases globally, unprecedented challenges are being faced,\ud which require modern, sophisticated methods to counter them. This calls for the use of automation in the\ud power system. The Supervisory Control and Data Acquisition (SCADA) and Programmable Logic\ud Controllers (PLC) are an answer to this.\ud SCADA refers to a system that enables on electricity utility to remotely monitor, co-ordinate,\ud control and operate transmission and distribution components, equipment and real-time mode from a\ud remote location with acquisition at date for analysis and planning from one control location.\ud PLC on the other hand is like the brain of the system with the joint operation of the SCADA\ud and the PLC, it is possible to control and operate the power system remotely. Task like\ud Opening of circuit breakers, changing transformer taps and managing the load demand can be carried out\ud efficiently.\ud This type of an automatic network can manage load, maintain quality, detect theft of\ud electricity and tempering of meters. It gives the operator an overall view of the entire network. Also, flow\ud of power can be closely scrutinized and Pilferage points can be located. Human errors leading to tripping\ud can be eliminated. This directly increases the reliability and lowers the operating cost.\ud In short our project is an integration of network monitoring functions with geographical\ud mapping, fault location, load management and intelligent metering

Research And Development Of Industrial Integrated Robotic Workcell And Robotrun Software For Academic Curriculum

Robotic automation is consuming the laborious tasks performed by workers all over industry. The increasing demand for trained robotic engineers to implement and maintain industrial robots has led to the development of various courses in academia. Michigan Tech is a FANUC Authorized Certified Education Training Center for industrial robot training. This report discusses the research and development of an integrated robotic workcell consisting of three Fanuc robots, Allen Bradley programmable logic controller (PLC), Mini-Mover belt conveyor and Fanuc iR-vision system. The workcell allows students to explore an environment similar to industry and intended to be used for laboratory hands-on activities in two robotic courses: Real-time Robotic Systems and Industrial Robotic Vision System. To complement hands-on activities and to meet the need of educating robotics to those without access to physical robots, an open source robotic simulation software RobotRun has been created in collaboration with a faculty member and students from Computer Science department. The features and a few training examples on the software have also been presented

The ARIEL Instrument Control Unit design for the M4 Mission Selection Review of the ESA's Cosmic Vision Program

The Atmospheric Remote-sensing Infrared Exoplanet Large-survey mission (ARIEL) is one of the three present candidates for the ESA M4 (the fourth medium mission) launch opportunity. The proposed Payload will perform a large unbiased spectroscopic survey from space concerning the nature of exoplanets atmospheres and their interiors to determine the key factors affecting the formation and evolution of planetary systems. ARIEL will observe a large number (>500) of warm and hot transiting gas giants, Neptunes and super-Earths around a wide range of host star types, targeting planets hotter than 600 K to take advantage of their well-mixed atmospheres. It will exploit primary and secondary transits spectroscopy in the 1.2-8 um spectral range and broad-band photometry in the optical and Near IR (NIR). The main instrument of the ARIEL Payload is the IR Spectrometer (AIRS) providing low-resolution spectroscopy in two IR channels: Channel 0 (CH0) for the 1.95-3.90 um band and Channel 1 (CH1) for the 3.90-7.80 um range. It is located at the intermediate focal plane of the telescope and common optical system and it hosts two IR sensors and two cold front-end electronics (CFEE) for detectors readout, a well defined process calibrated for the selected target brightness and driven by the Payload's Instrument Control Unit (ICU).Comment: Experimental Astronomy, Special Issue on ARIEL, (2017