Terminology and Symbols in Control Engineering
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Actuator Product Guide
About Moog Multi-purpose Actuators and Servoactuators Moog’s multi-purpose actuators and servoactuators can be used for a variety of high performance applications and are standard building blocks used in ruggedized systems. We utilize our expertise in DC electromagnetics, gearing, rate and position loop servo electronics and mechanical design in these assemblies. Moog rotary and linear electromechancial actuators are used in: • Fixed and Rotary Wing Aircrafts • Unmanned Vehicles / Remotely Operated Vehicles • Ground Vehicles • Radar Systems • Remote Weapon Stations • SATCOM Pedestals • EO / IR Sensor Pods • Cockpit Door Locks • Valve / Damper Actuators Capability Moog has been developing specialized high technology and utility electromechanical actuators for over 25 years. Our capability includes in-house design, manufacturing expertise, engineering support and qualification for these products. Product Range Products range from 25 to 2,500 in-lbt for rotary and 100 to 2,000 lbf for linear configurations. We can offer our assemblies with integral servo control electronics. Moog offers a variety of communication interfaces including analog, (+/- 10 VDC for example), RS232 / 422 / 485, R/C PWM and CAN Bus. We design for redundancy as required by the customer. Moog is a FAA certified repair station and can offer hardware in support of AOG services. FAA / EASA Approved Repair Station Location, Springfield, PA FAA Repair Station: L17R251Y 750 West Sproul Road EASA (JAA): 145.5497 Springfield, PA 19064-4084 USA Cage Code: 1K426 Tel: +1-610-328-4000 Fax: +1-610-605-6216 FAA / EASA Approved Repair Station Location, Blacksburg, VA FAA Repair Station: 21MR057C 1213 North Main Street Cage Code: 99932 Blacksburg VA 24060-3127 USA Tel: +1-540-552-3011 Fax: +1-540-557-6719 2 Moog • www.moog.com Rotary Actuators Rotary Actuators Rotary servoactuators utilize brush and brushless type DC motors using both neodymium and rare earth magnets. -
Metallurgical Engineering
ENSURING THE EXPERTISE TO GROW SOUTH AFRICA Discipline-specific Training Guideline for Candidate Engineers in Metallurgical Engineering R-05-MET-PE Revision No.: 2: 25 July 2019 ENGINEERING COUNCIL OF SOUTH AFRICA Tel: 011 6079500 | Fax: 011 6229295 Email: [email protected] | Website: www.ecsa.co.za ENSURING THE Document No.: Effective Date: Revision No.: 2 R-05-MET-PE 25/07/2019 Subject: Discipline-specific Training Guideline for Candidate Engineers in Metallurgical Engineering Compiler: Approving Officer: Next Review Date: Page 2 of 46 MB Mtshali EL Nxumalo 25/07/2023 TABLE OF CONTENTS DEFINITIONS ............................................................................................................................ 3 BACKGROUND ......................................................................................................................... 5 1. PURPOSE OF THIS DOCUMENT ......................................................................................... 5 2. AUDIENCE............................................................................................................................. 6 3. PERSONS NOT REGISTERED AS CANDIDATES OR NOT BEING TRAINED UNDER COMMITMENT AND UNDERTAKING (C&U) ..................................................... 7 4. ORGANISING FRAMEWORK FOR OCCUPATIONS ............................................................. 7 4.1 Extractive Metallurgical Engineering ..................................................................................... 8 4.2 Mineral Processing Engineering .......................................................................................... -
Control in Robotics
Control in Robotics Mark W. Spong and Masayuki Fujita Introduction The interplay between robotics and control theory has a rich history extending back over half a century. We begin this section of the report by briefly reviewing the history of this interplay, focusing on fundamentals—how control theory has enabled solutions to fundamental problems in robotics and how problems in robotics have motivated the development of new control theory. We focus primarily on the early years, as the importance of new results often takes considerable time to be fully appreciated and to have an impact on practical applications. Progress in robotics has been especially rapid in the last decade or two, and the future continues to look bright. Robotics was dominated early on by the machine tool industry. As such, the early philosophy in the design of robots was to design mechanisms to be as stiff as possible with each axis (joint) controlled independently as a single-input/single-output (SISO) linear system. Point-to-point control enabled simple tasks such as materials transfer and spot welding. Continuous-path tracking enabled more complex tasks such as arc welding and spray painting. Sensing of the external environment was limited or nonexistent. Consideration of more advanced tasks such as assembly required regulation of contact forces and moments. Higher speed operation and higher payload-to-weight ratios required an increased understanding of the complex, interconnected nonlinear dynamics of robots. This requirement motivated the development of new theoretical results in nonlinear, robust, and adaptive control, which in turn enabled more sophisticated applications. Today, robot control systems are highly advanced with integrated force and vision systems. -
Modern Design and Control of Automatic Transmission and The
Review Paper doi:10.5937/jaes13-7727 Paper number: 13(2015)1, 313, 51 - 59 MODERN DESIGN AND CONTROL OF AUTOMATIC TRANSMISSION AND THE PROSPECTS OF DEVELOPMENT Dejan Matijević The School of Electrical and Computer Engineering of Applied Studies, Belgrade, Serbia Ivan Ivanković* University of Belgrade, Faculty of Mechanical Engineering, Belgrade, Serbia Dr Vladimir Popović University of Belgrade, Faculty of Mechanical Engineering, Belgrade, Serbia The paper provides an overview of modern technical solutions of automatic transmissions in auto- motive industry with their influence on sustainable development. The objective of the first section is a structural view of specific constructions and control systems of presently used automatic transmis- sions, with emphasis on mechatronics implementation. The second section is based on perspectives of development, by integrating some branches of soft computing, such as fuzzy logic and artificial neural networks in order to create an optimal control algorithm for obtaining a contribution to fuel economy, exhaust emission, comfort and vehicle performance. Key words: Automatic transmission, Mechatronics, Automotive industry, Soft Computing INTRODUCTION which is depended by coefficient of friction and normal load on the drive axle. Lower limitation Almost all automobiles in use today are driven by is defined by maximal speed that vehicle can internal combustion engines, which are charac- reach. Shaded areas between traction forces terized by many advantages, such as relatively through gears are power losses. To decrease good efficiency, relatively compact energy stor- power losses and to be as closely as possible age and high power – to – weight ratio [07]. to the ideal traction hyperbola, the gearbox with But, fundamental disadvantages are: enough gear ratios is needed. -
Radar Transmitter/Receiver
Introduction to Radar Systems Radar Transmitter/Receiver Radar_TxRxCourse MIT Lincoln Laboratory PPhu 061902 -1 Disclaimer of Endorsement and Liability • The video courseware and accompanying viewgraphs presented on this server were prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, nor the Massachusetts Institute of Technology and its Lincoln Laboratory, nor any of their contractors, subcontractors, or their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, products, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government, any agency thereof, or any of their contractors or subcontractors or the Massachusetts Institute of Technology and its Lincoln Laboratory. • The views and opinions expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or any of their contractors or subcontractors Radar_TxRxCourse MIT Lincoln Laboratory PPhu 061802 -2 Outline • Introduction • Radar Transmitter • Radar Waveform Generator and Receiver • Radar Transmitter/Receiver Architecture -
Technical Report 05-73 the Methodology Center, Pennsylvania State University
Engineering Control Approaches for the Design and Analysis of Adaptive, Time-Varying Interventions Daniel E. Rivera and Michael D. Pew Control Systems Engineering Laboratory Department of Chemical and Materials Engineering Arizona State University Tempe, Arizona 85287-6006 Linda M. Collins The Methodology Center and Department of Human Development and Family Studies Penn State University State College, PA Susan A. Murphy Institute for Social Research and Department of Statistics University of Michigan Ann Arbor, MI May 30, 2005 Technical Report 05-73 The Methodology Center, Pennsylvania State University 1 Abstract Control engineering is the field that examines how to transform dynamical system behavior from undesirable conditions to desirable ones. Cruise control in automobiles, the home thermostat, and the insulin pump are all examples of control engineering at work. In the last few decades, signifi- cant improvements in computing and information technology, increasing access to information, and novel methods for sensing and actuation have enabled the extensive application of control engi- neering concepts to physical systems. While engineering control principles are meaningful as well to problems in the behavioral sciences, the application of this topic to this field remains largely unexplored. This technical report examines how engineering control principles can play a role in the be- havioral sciences through the analysis and design of adaptive, time-varying interventions in the prevention field. The basic conceptual framework for this work draws from the paper by Collins et al. (2004). In the initial portion of the report, a general overview of control engineering principles is presented and illustrated with a simple physical example. From this description, a qualitative description of adaptive time-varying interventions as a form of classical feedback control is devel- oped, which is depicted in the form of a block diagram (i.e., a control-oriented signal and systems representation). -
An Overview of Novel Actuators for Soft Robotics
actuators Review An Overview of Novel Actuators for Soft Robotics Pinar Boyraz 1,2,* ID , Gundula Runge 3 and Annika Raatz 3 1 Mechanics and Maritime Sciences Department, Chalmers University of Technology, 41296 Gothenburg, Sweden 2 Mechanical Engineering Department, Istanbul Technical University, Istanbul 34437, Turkey 3 Institut fur Montagetechnik (match), Leibniz Universität Hannover, 30823 Garbsen, Hannover, Germany; [email protected] (G.R.); [email protected] (A.R.) * Correspondence: [email protected]; Tel.: +46-730-49-8780 Received: 10 June 2018; Accepted: 9 August 2018; Published: 16 August 2018 Abstract: In this systematic survey, an overview of non-conventional actuators particularly used in soft-robotics is presented. The review is performed by using well-defined performance criteria with a direction to identify the exemplary and potential applications. In addition to this, initial guidelines to compare the performance and applicability of these novel actuators are provided. The meta-analysis is restricted to five main types of actuators: shape memory alloys (SMAs), fluidic elastomer actuators (FEAs), shape morphing polymers (SMPs), dielectric electro-activated polymers (DEAPs), and magnetic/electro-magnetic actuators (E/MAs). In exploring and comparing the capabilities of these actuators, the focus was on eight different aspects: compliance, topology-geometry, scalability-complexity, energy efficiency, operation range, modality, controllability, and technological readiness level (TRL). The overview presented here provides a state-of-the-art summary of the advancements and can help researchers to select the most convenient soft actuators using the comprehensive comparison of the suggested quantitative and qualitative criteria. Keywords: soft-robotics; actuator performance; SMA; SMP; FEA; DEAP; E/MA 1. -
Exlar Electric Test and Simulation Actuator Systems
Delivering more accurate and trouble-free test actuators. Exlar Electric Test and Simulation Actuator Systems Courtesy of Steven Engineering, Inc. - 230 Ryan Way, South San Francisco, CA 94080-5370 - Main Office: (650) 588-9200 - Outside Local Area: (800) 258-9200 - www.stevenengineering.com entertainment simulators, Exlar actutors are Paradigm Shift ergonomic endurance directly controlled in Mechanical test equipment, geo- by the system’s logical test equipment, electric servo Testing System wear testing, and even amplifi er. No Technology aircraft structural testing intermediary such and dynamic simulation. as oil or air is required to create Historically, manufacturers and motion. System users of mechanical test ap- The Benefi ts compliance result- paratus and motion simulators ing from use of have accepted the inaccuracies, of All-Electric fl uid power is a inconvenience and high mainte- Test Actuator major contributor nance costs of hydraulic actua- to inaccuracy of tion. However, today’s simula- Systems tors and test stands are often hydraulic actua- Exlar’s patented roller used in environments where tor systems. The screw linear actuator contamination from oil leaks is higher stiffness of technology allows users to not permissable and greater ac- a planetary perform the analysis and testing curacy is required. Exlar offers roller screw-based actuator pro- needed to verify products’ de- a full range of all-electric test vides greater system response actuators and position controls signs without the high cost of in- and stability assuring precise which provide the dynamic per- stallation, constant maintenance, and crisp control, and stiffness formance and long life required environmental issues, and en- is not stroke-sensitive. -
A Process Control Primer
A Process Control Primer Sensing and Control Copyright, Notices, and Trademarks Printed in U.S.A. – © Copyright 2000 by Honeywell Revision 1 – July 2000 While this information is presented in good faith and believed to be accurate, Honeywell disclaims the implied warranties of merchantability and fitness for a particular purpose and makes no express warranties except as may be stated in its written agreement with and for its customer. In no event is Honeywell liable to anyone for any indirect, special or consequential damages. The information and specifications in this document are subject to change without notice. Presented by: Dan O’Connor Sensing and Control Honeywell 11 West Spring Street Freeport, Illinois 61032 UDC is a trademark of Honeywell Accutune is a trademark of Honeywell ii Process Control Primer 7/00 About This Publication The automatic control of industrial processes is a broad subject, with roots in a wide range of engineering and scientific fields. There is really no shortcut to an expert understanding of the subject, and any attempt to condense the subject into a single short set of notes, such as is presented in this primer, can at best serve only as an introduction. However, there are many people who do not need to become experts, but do need enough knowledge of the basics to be able to operate and maintain process equipment competently and efficiently. This material may hopefully serve as a stimulus for further reading and study. 7/00 Process Control Primer iii Table of Contents CHAPTER 1 – INTRODUCTION TO PROCESS -
Programmable Logic Controller
Revised 10/07/19 SPECIFICATIONS - DETAILED PROVISIONS Section 17010 - Programmable Logic Controller C O N T E N T S PART 1 - GENERAL ....................................................................................................................... 1 1.01 DESCRIPTION .............................................................................................................. 1 1.02 RELATED SECTIONS ...................................................................................................... 1 1.03 REFERENCE STANDARDS AND CODES ............................................................................ 2 1.04 DEFINITIONS ............................................................................................................... 2 1.05 SUBMITTALS ............................................................................................................... 3 1.06 DESIGN REQUIREMENTS .............................................................................................. 8 1.07 INSTALLED-SPARE REQUIREMENTS ............................................................................. 13 1.08 SPARE PARTS............................................................................................................. 13 1.09 MANUFACTURER SERVICES AND COORDINATION ........................................................ 14 1.10 QUALITY ASSURANCE................................................................................................. 15 PART 2 - PRODUCTS AND MATERIALS......................................................................................... -
Lecture 11 : Discrete Cosine Transform Moving Into the Frequency Domain
Lecture 11 : Discrete Cosine Transform Moving into the Frequency Domain Frequency domains can be obtained through the transformation from one (time or spatial) domain to the other (frequency) via Fourier Transform (FT) (see Lecture 3) — MPEG Audio. Discrete Cosine Transform (DCT) (new ) — Heart of JPEG and MPEG Video, MPEG Audio. Note : We mention some image (and video) examples in this section with DCT (in particular) but also the FT is commonly applied to filter multimedia data. External Link: MIT OCW 8.03 Lecture 11 Fourier Analysis Video Recap: Fourier Transform The tool which converts a spatial (real space) description of audio/image data into one in terms of its frequency components is called the Fourier transform. The new version is usually referred to as the Fourier space description of the data. We then essentially process the data: E.g . for filtering basically this means attenuating or setting certain frequencies to zero We then need to convert data back to real audio/imagery to use in our applications. The corresponding inverse transformation which turns a Fourier space description back into a real space one is called the inverse Fourier transform. What do Frequencies Mean in an Image? Large values at high frequency components mean the data is changing rapidly on a short distance scale. E.g .: a page of small font text, brick wall, vegetation. Large low frequency components then the large scale features of the picture are more important. E.g . a single fairly simple object which occupies most of the image. The Road to Compression How do we achieve compression? Low pass filter — ignore high frequency noise components Only store lower frequency components High pass filter — spot gradual changes If changes are too low/slow — eye does not respond so ignore? Low Pass Image Compression Example MATLAB demo, dctdemo.m, (uses DCT) to Load an image Low pass filter in frequency (DCT) space Tune compression via a single slider value n to select coefficients Inverse DCT, subtract input and filtered image to see compression artefacts. -
Control Theory
Control theory S. Simrock DESY, Hamburg, Germany Abstract In engineering and mathematics, control theory deals with the behaviour of dynamical systems. The desired output of a system is called the reference. When one or more output variables of a system need to follow a certain ref- erence over time, a controller manipulates the inputs to a system to obtain the desired effect on the output of the system. Rapid advances in digital system technology have radically altered the control design options. It has become routinely practicable to design very complicated digital controllers and to carry out the extensive calculations required for their design. These advances in im- plementation and design capability can be obtained at low cost because of the widespread availability of inexpensive and powerful digital processing plat- forms and high-speed analog IO devices. 1 Introduction The emphasis of this tutorial on control theory is on the design of digital controls to achieve good dy- namic response and small errors while using signals that are sampled in time and quantized in amplitude. Both transform (classical control) and state-space (modern control) methods are described and applied to illustrative examples. The transform methods emphasized are the root-locus method of Evans and fre- quency response. The state-space methods developed are the technique of pole assignment augmented by an estimator (observer) and optimal quadratic-loss control. The optimal control problems use the steady-state constant gain solution. Other topics covered are system identification and non-linear control. System identification is a general term to describe mathematical tools and algorithms that build dynamical models from measured data.