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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......................................................................................... -
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. -
Overview of Distributed Control Systems Formalisms 253
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by DSpace at VSB Technical University of Ostrava Overview of distributed control systems formalisms 253 OVERVIEW OF DISTRIBUTED CONTROL SYSTEMS FORMALISMS P. Holeko Department of Control and Information Systems, Faculty of Electrical Engineering, University of Žilina Univerzitná 8216/1, SK 010 26, Žilina, Slovak republic, tel.: +421 41 513 3343, e-mail: [email protected] Summary This paper discusses a chosen set of mainly object-oriented formal and semiformal methods, methodics, environments and tools for specification, analysis, modeling, simulation, verification, development and synthesis of distributed control systems (DCS). 1. INTRODUCTION interconnected by a network for the purpose of communication and monitoring. Increasing demands on technical parameters, In the next section the problem of formalizing reliability, effectivity, safety and other the processes of DCS’s life-cycle will be discussed. characteristics of industrial control systems initiate distribution of its control components across the 3. FORMAL METHODS plant. The complexity requires involving of formal The main motivations of using formal concepts methods in the process of specification, analysis, are [9]: modeling, simulation, verification, development, and ° In the process of formalizing informal in the optimal case in synthesis of such systems. requirements, ambiguities, omissions and contradictions will often be discovered; 2. DISTRIBUTED CONTROL SYSTEM ° The formal model -
Development of the Software Tools Using Python for Epics-Based Control System T
TPPA16 Proceedings of ICALEPCS07, Knoxville, Tennessee, USA DEVELOPMENT OF THE SOFTWARE TOOLS USING PYTHON FOR EPICS-BASED CONTROL SYSTEM T. T. Nakamura, K. Furukawa, J-I. Odagiri, N. Yamamoto, KEK, Tsukuba, Ibaraki, Japan Abstract Basic functions of CA are get, put, and monitor In the commissioning phase of accelerators, many operations. List 1 shows an example of get operation of application programs are built and modified frequently by Python-CA. Module name of Python-CA is “ca”, which nonexpert programmers. Scripting language such as appears in import statement. Python is suitable for such quick development. Since List 1: Example of Python-CA (get operation) EPICS Channel Access interface library in Python was import ca developed in KEKB accelerator control system, many programs has been written in Python. We have been chan = ca.channel("channel_name") developing, providing some tools and libraries for Python chan.wait_conn() programming. Some of the recent developments in KEK chan.get() are reported, and possible applications are also discussed. ca.pend_event(1.0) value = chan.val INTRODUCTION KEKB is an asymmetric electron-positron collider at 8 Simple-CA library × 3.5 GeV/c, which is dedicated to B-meson physics. Its While Python-CA provides powerful functions of CA operation was started in December 1998. The KEKB client library, most people still feels complexity for CA accelerators control system has been constructed based on programming. List 1 show that even for single get EPICS (Experimental Physics and Industrial Control operation it needs 4 function (or method) calls. System) tool kit [1]. EPICS provides core mechanism for We have also developed Simple-CA library, which is a the distributed control system. -
Introduction to Feedback Control
ECE4510/5510: Feedback Control Systems. 1–1 INTRODUCTION TO FEEDBACK CONTROL 1.1: What is feedback control? I Control-system engineers often face this question (or, “What is it that you do, anyway?”) when trying to explain their professional field. I Loosely speaking, control is the process of getting “something” to do what you want it to do (or “not do,” as the case may be). The “something” can be almost anything. Some obvious • examples: aircraft, spacecraft, cars, machines, robots, radars, telescopes, etc. Some less obvious examples: energy systems, the economy, • biological systems, the human body. I Control is a very common concept. e.g.,Human-machineinteraction:Drivingacar. ® Manual control. e.g.,Independentmachine:Roomtemperaturecontrol.Furnacein winter, air conditioner in summer. Both controlled (turned “on”/“off”) by thermostat. (We’ll look at this example more in Topic 1.2.) ® Automatic control (our focus in this course). DEFINITION: Control is the process of causing a system variable to conform to some desired value, called a reference value. (e.g., variable temperature for a climate-control system) = Lecture notes prepared by and copyright c 1998–2013, Gregory L. Plett and M. Scott Trimboli ! ECE4510/ECE5510, INTRODUCTION TO FEEDBACK CONTROL 1–2 tp Mp I Usually defined in terms 1 0.9 of the system’s step re- sponse, as we’ll see in notes Chapter 3. 0.1 t tr ts DEFINITION: Feedback is the process of measuring the controlled variable (e.g.,temperature)andusingthatinformationtoinfluencethe value of the controlled variable. I Feedback is not necessary for control. But, it is necessary to cater for system uncertainty, which is the principal role of feedback. -
Pure Labview Implementation of EPICS Communication Protocol
Pure LabVIEW Implementation of EPICS Communication Protocol Alexander Zhukov Spallation Neutron Source, ORNL NIWeek 2012 Managed by UT-Battelle for the Department of Energy What is EPICS Experimental Physics and Industrial Control System (EPICS) is a set of Open Source software tools, libraries and applications developed collaboratively and used worldwide to create distributed soft real-time control systems for scientific instruments such as a particle accelerators, telescopes and other large scientific experiments. Major collaborators – ANL – LANL – ORNL (SNS) – SLAC (SSRL, LCLS) – JLAB (CEBAF) – DESY – BESSY – PSI (SLS) – KEK Runs on variety of hardware/OS (Linux, VxWorks, Windows, Mac, RTEMS…) 2 Managed by UT-Battelle for the Department of Energy How EPICS works A network based fully distributed client/server model Client and server use Channel Access (CA) protocol to communicate Everything spins around process variables (PV) – an entity similar to LabVIEW network shared variable – A server (Input Output Controller – IOC) publishes data by updating PVs – PV corresponds to some value (measurement, setting, status etc) – Every PV has unique name – Client has ways to read PVs and update them over network – Client can subscribe to particular PV and monitor its value or state without polling it Standard EPICS server also has records processing mechanism – Control logic is programmed in records definition file – Allows perform routine tasks without explicitly programming in C – In addition to value every record has also status (OK, -
EPICS Application Developer's Guide
1 EPICS Application Developer’s Guide EPICS Base Release 3.15.0.2 17 October 2014 Andrew N. Johnson, Janet B. Anderson, Martin R. Kraimer (Argonne National Laboratory) W. Eric Norum (Lawrence Berkeley National Laboratory) Jeffrey O. Hill (Los Alamos National Laboratory) Ralph Lange, Benjamin Franksen (Helmholtz-Zentrum Berlin) Peter Denison (Diamond Light Source) 2 Contents EPICS Applications Developer’s Guide1 Table of Contents 7 1 Introduction 9 1.1 Overview.................................................9 1.2 Acknowledgments............................................ 11 2 Getting Started 13 2.1 Introduction................................................ 13 2.2 Example IOC Application........................................ 13 2.3 Channel Access Host Example...................................... 15 2.4 iocsh.................................................... 16 2.5 Building IOC components........................................ 16 2.6 makeBaseApp.pl............................................. 19 2.7 vxWorks boot parameters......................................... 22 2.8 RTEMS boot procedure.......................................... 23 3 EPICS Overview 25 3.1 What is EPICS?.............................................. 25 3.2 Basic Attributes.............................................. 26 3.3 IOC Software Components........................................ 26 3.4 Channel Access.............................................. 28 3.5 OPI Tools................................................. 30 3.6 EPICS Core Software.......................................... -
8. Feedback Control Systems
feedback control - 8.1 8. FEEDBACK CONTROL SYSTEMS Topics: • Transfer functions, block diagrams and simplification • Feedback controllers • Control system design Objectives: • To be able to represent a control system with block diagrams. • To be able to select controller parameters to meet design objectives. 8.1 INTRODUCTION Every engineered component has some function. A function can be described as a transformation of inputs to outputs. For example it could be an amplifier that accepts a sig- nal from a sensor and amplifies it. Or, consider a mechanical gear box with an input and output shaft. A manual transmission has an input shaft from the motor and from the shifter. When analyzing systems we will often use transfer functions that describe a sys- tem as a ratio of output to input. 8.2 TRANSFER FUNCTIONS Transfer functions are used for equations with one input and one output variable. An example of a transfer function is shown below in Figure 8.1. The general form calls for output over input on the left hand side. The right hand side is comprised of constants and the ’D’ operator. In the example ’x’ is the output, while ’F’ is the input. The general form An example output x 4 + D ----------------- = fD() --- = --------------------------------- input F D2 ++4D 16 Figure 8.1 A transfer function example feedback control - 8.2 If both sides of the example were inverted then the output would become ’F’, and the input ’x’. This ability to invert a transfer function is called reversibility. In reality many systems are not reversible. There is a direct relationship between transfer functions and differential equations. -
(5) Type of Control Components, (6) Basic Control System, (7) Automatic
F DOCV4F NT R F S 1,4 F ED 023 279 EF 002 096 Temperature Control. Honeywell Planning Guide. Honeywell, Minneapolis, Minn. Pub Date Mar 68 Note -26p. EORS Price MF -S025 HC -$I AO Descriptors -Building Eluipment, *Climate Control, *ControlledEnvironment, Guidelines, *Mechanical Equipment , *Temperature, Themil Environment Identifiers -Honeywell Presentsplanningconsiderations inselectingproper temperaturecontrol systems. Various aspects are discussedincluding--(1) adequate environmental control, (2) adequate control area, (3) control system design, (4) operators ratetheir systems, (5) type of control components, (6) basic control system,(7) automatic control systems, and (8) variables that affect systemperformance. (RH) U.S. DEPARTMENT Of HEALTH. EDUCATION & WELFARE OFFICE OF EDUCATION THIS DOCUMENT HAS BEEN REPRODUCED EXACTLY AS RECEIVED FROM THE PERSON OR ORGANIZATION ORIGINATING IT.POINTS OF VIEW OR OPINIONS STATED DO NOT NECESSARILY REPRESENT OFFICIAL OFFICE OF EDUCATION POSITION OR POLICY. 0144 '4; A xfr/. HONEYWELL PLANNING GUIDE TEMPERATURE CONTROL Man's own environment: The indoor airwe breathe, work in, play in, sleep and eat in. We heat it, cool it, dry it, addmoisture to it. It commands more of our attention each day. And wellit should. Tests have shown that it afiectsour productivity, our attitudes, our safety, even the way we think and learn. In fact,the implications of indoor environment, the atmospherewe can control, are as practical and sophisticated as today's imaginative buildingarchitecture and its multiple uses. Today, environmental control design andapplica- tion deserves the serious consideration of buildingowners, builders, engineers, and architects as wellas control system manufacturers. Choosing the proper environmental controlsystem presents a quan- dary of choice for the commercial buildingowner or builder. -
EPICS at Fermilab: Not Just D0 Anymore - Cavities, Cavities, Cavities
EPICS at Fermilab: Not just D0 anymore - Cavities, Cavities, Cavities Geoff Savage for the Dzero and ILCTA controls groups Wed June 14, 2006 EPICS Collaboration Meeting Current EPICS Projects Run II Experiments D0 Controls. ILC Test Accelerator (ILCTA) @ FNAL Cavity testing in three facilities, maybe a fourth Horizontal Test Facility/Coupler conditioning (MDB) Run tests in August 2006 Vertical Test Facility (IB1) Getting started Beam test (NML) using photoinjector currently at A0 Preparing facility - cryo installed at the end of 2007 Other Proton Driver – EPICS only control system Nova – Seriously evaluating EPICS as control system for DAQ. Maybe also for controls itself? 6/14/2006 EPICS Collaboration Mtg 2 D0 Detector Increased luminosity in Run IIb Just finished detector upgrade Silicon layer 0 Enhanced triggering systems Goals for controls Support new field busses Remove 68k processors from system Move to EPICS 3.14.8.2 Controls - all EPICS all the time DAQ controls are independent 6/14/2006 EPICS Collaboration Mtg 3 D0 Controls Two new field buses CANbus driver wrapped in ASYN TPMC816 - dual channel PMC CANbus module Implements limited CANbus feature set Raw ethernet driver in ASYN Linux IOC connected via fiber to remote crate Trying to get to 3.14.8.2 Tested but not deployed Currently using 3.14.6 and 3.13.4 MVME5500 processors Remove remaining 68k processors ~ 25 Some problems - similar experiences? 6/14/2006 EPICS Collaboration Mtg 4 ILCTA Controls Systems ACNET (FNAL) Accelerator Division Drivers/interfaces for FNAL devices already written and in use at Fermilab in ILCTA (HRM) EPICS (ANL) Cryogenics interface for MDB and NML. -
Control System Design Methods
Christiansen-Sec.19.qxd 06:08:2004 6:43 PM Page 19.1 The Electronics Engineers' Handbook, 5th Edition McGraw-Hill, Section 19, pp. 19.1-19.30, 2005. SECTION 19 CONTROL SYSTEMS Control is used to modify the behavior of a system so it behaves in a specific desirable way over time. For example, we may want the speed of a car on the highway to remain as close as possible to 60 miles per hour in spite of possible hills or adverse wind; or we may want an aircraft to follow a desired altitude, heading, and velocity profile independent of wind gusts; or we may want the temperature and pressure in a reactor vessel in a chemical process plant to be maintained at desired levels. All these are being accomplished today by control methods and the above are examples of what automatic control systems are designed to do, without human intervention. Control is used whenever quantities such as speed, altitude, temperature, or voltage must be made to behave in some desirable way over time. This section provides an introduction to control system design methods. P.A., Z.G. In This Section: CHAPTER 19.1 CONTROL SYSTEM DESIGN 19.3 INTRODUCTION 19.3 Proportional-Integral-Derivative Control 19.3 The Role of Control Theory 19.4 MATHEMATICAL DESCRIPTIONS 19.4 Linear Differential Equations 19.4 State Variable Descriptions 19.5 Transfer Functions 19.7 Frequency Response 19.9 ANALYSIS OF DYNAMICAL BEHAVIOR 19.10 System Response, Modes and Stability 19.10 Response of First and Second Order Systems 19.11 Transient Response Performance Specifications for a Second Order -
REALIZATION of LINUX PLATFORM in DISTRIBUTED CONTROL SYSTEM by EPICS at BEPCII Zhuo Zhao, C.H.Wang, Ge Lei, J.J.Zhao, K.J.Yue, Jia Liu, IHEP, Beijing, China
Proceedings of ICALEPCS2003, Gyeongju, Korea REALIZATION OF LINUX PLATFORM IN DISTRIBUTED CONTROL SYSTEM BY EPICS AT BEPCII Zhuo Zhao, C.H.Wang, Ge Lei, J.J.Zhao, K.J.Yue, Jia Liu, IHEP, Beijing, China Abstract also has friendly operating interface and it supports IHEP will begin the BEPCII project that has been software transplanting. funded by the Chinese Government in order to further At present, Red Hat Linux has developed release 9. So I upgrade the BEPC (Beijing Electron Positron Collider) select the latest release-Red Hat Linux 9 as the operating which has operated since 1989 [1]. As a part of this system that is installed on PC [4]. updating project, control system is decided to use EPICS The installing of ftp server and downloading of [2]. EPICS IOCs can run on many kinds of operating systems [3], for example VxWorks, Unix, Linux, VxWorks kernel Windows, RTEMS and so on. Based on the idea of After the Red Hat Linux 9 has been installed on one creating EPICS OPI on Linux and downloading real-time PC, ftp server should be also installed and started. The ftp database to VME IOC target board, this article is mainly server that I select is vsftpd whose “.rpm” instalation file about how to setup EPICS base and EPICS extension on is included in the Red Hat Linux 9’s installation Linux operating system and furthermore how to finish CDROM. communication between server and Linux control The VxWorks boot file should be in the special platform. In order to come into being a friendly directory in order to download VxWorks kernel.