DISTRIBUTED CONTROL SYSTEMS

DISTRIBUTED CONTROL SYSTEMSA distributed control system (DCS) is a control system for a process or plant, wherein control elements are distributed throughout the system. This is in contrast to non-distributed systems, which use a single controller at a central location. In a DCS, a hierarchy of controllers is connected by communications networks for command and monitoring. Example scenarios where a DCS might be used include: Chemical plants Petrochemical (oil) and refineries Pulp and Paper Mills Boiler controls and power plant systems Nuclear power plants Environmental control systems Water management systems Metallurgical process plants Pharmaceutical manufacturing Sugar refining plants Dry cargo and bulk oil carrier ships Formation control of multi-agent systems. ELEMENTS OF DCSA DCS typically uses custom designed processors as controllers and uses both proprietary interconnections and standard communications protocol for communication. Input and output modules form component parts of the DCS. The processor receives information from input modules and sends information to output modules. The input modules receive information from input instruments in the process (or field) and the output modules transmit instructions to the output instruments in the field. The inputs and outputs can be either analog signal which are continuously changing or discrete signals which are 2 state either on or off . Computer buses or electrical buses connect the processor and modules through multiplexer or demultiplexers. Buses also connect the distributed controllers with the central controller and finally to the Human– machine interface (HMI) or control consoles. See Process automation systems.

The elements of a DCS may connect directly to physical equipment such as switches, pumps and valves and to Human Machine Interface (HMI) via SCADA. The differences between a DCS and SCADA is often subtle, especially with advances in technology allowing the functionality of each to overlap.

Engineering PC or controllerThis controller is the supervisory controller over all the distributed processing controllers. Control algorithms and configuration of various devices are executed in this controller. Network communication between processing and engineering PC can be implemented by simplex or redundant configurations. Distributed controller or Local control unitIt can be placed near to field devices (sensors and actuators) or certain location where these field devices are connected via communication link. It receives the instructions from the engineering station like set point and other parameters and directly controls field devices. It can sense and control both analog and digital inputs / outputs by analog and digital I/O modules. These modules are extendable according to the number of inputs and outputs. It collects the information from discrete field devices and sends this information to operating and engineering stations. In above figure AC 700F and AC 800Fcontrollers acts as communication interface between field devices and engineering station. Most of the cases these act as local control for field instruments. Operating station or HMIIt is used to monitor entire plant parameters graphically and to log the data in plant database systems. Trend display of various process parameters provides the effective display and easy monitoring. These operating stations are of different types such as some operating stations (PC’s) used to monitor only parameters, some for only trend display, some for data logging and alarming requirements. These can also be configured to have control capabilities. Communication media and protocolCommunication media consists of transmission cables to transmit the data such as coaxial cables, copper wires, fiber optic cables and sometimes it might be wireless. Communication protocols selected depends on the number of devices to be connected to this network. For example, RS232 supports only for 2 devices and Profibus for 126 devices or nodes. Some of these protocols include Ethernet, DeviceNet, foundation filed bus, modbus, CAN, etc. In DCS, two or more communication protocols are used in between two or more areas such as between field control devices and distributed controllers and other one between distributed controllers and supervisory control stations such as operating and engineering stations.

Important features of DCS • To handle complex processes: In factory automation structure, PLC-Programming Logic Controller is used to control and monitor the process parameters at high speed requirements. However due to limitation of number of I/O devices, PLC’s cannot handle complex structure. Hence DCS is preferred for complex control applications with more number of I/O’s with dedicated controllers. These are used in manufacturing processes where designing of multiple products are in multiple procedures such as batch process control. System redundancy:

System Redundancy DCS facilitates system availability when needed by redundant feature at every level. Resuming of the steady state operation after any outages, whether planned or unplanned is somewhat better compared to other automation control devices. Redundancy raises the system reliability by maintaining system operation continuously even in some abnormalities while system is in operation. Lot of Predefined function blocks:

Predefined Function block DCS offers many algorithms, more standard application libraries, pre-tested and pre-defined functions to deal with large complex systems. This makes programming to control various applications being easy and consuming less time to program and control. Powerful programming languages: It provides more number of programming languages like ladder, function block, sequential, etc for creating the custom programming based on user interest. More sophisticated HMI: Similar to the SCADA system, DCS can also monitor and control through HMI’s (Human Machine Interface) which provides sufficient data to the operator to charge over various processes and it acts as heart of the system. But this type of industrial control system covers large geographical areas whereas DCS covers confined area.

DCS completely takes the entire process plant to control room as a PC window. Trending, logging and graphical representation of the HMI’s give effective user interface. Powerful alarming system of DCS helps operators to respond more quickly to the plant conditions Scalable platform: Structure of DCS can be scalable based on the number I/O’s from small to large server system by adding more number of clients and servers in communication system and also by adding more I/O modules in distributed controllers. System security: Access to control various processes leads to plant safety. DCS design offers perfect secured system to handle system functions for better factory automation control. Security is also provided at different levels such as engineer level, entrepreneur level, operator level, etc.

DATA ACQUISITION BASICSData acquisition is the process of sampling signals that measure real world physical conditions and converting the resulting samples into digital numeric values that can be manipulated by a computer. Data acquisition systems, abbreviated by the acronym DAS or DAQ typically convert analog waveforms into digital values for processing. The components of data acquisition systems include: 1- Sensors: To convert physical parameters to electrical signals. 2-Signal conditioning circuitry: To convert sensor signals into a form that can be converted to digital values. 3-Analog-to-digital converters: to convert conditioned sensor signals to digital values. Data acquisition applications are usually controlled by software programs developed using various general purpose programming languages such as Assembly, BASIC, C, C++, C#, Fortran, Java, LabVIEW, Lisp, Pascal, etc. Stand-alone data acquisition systems are often called data loggers. There are also open-source software packages providing all the necessary tools to acquire data from different hardware equipment. These tools come from the scientific community where complex experiment requires fast, flexible and adaptable software. Those packages are usually

custom fit but more general DAQ package like the Maximum Integrated Data Acquisition System can be easily tailored and is used in several physics experiments worldwide.

HISTORYIn 1963, IBM produced computers which specialized in data acquisition. These include the IBM 7700 Data Acquisition System, and its successor, the IBM 1800 Data Acquisition and Control System. These expensive specialized systems were surpassed in 1974 by general purpose S-100 computers and data acquisitions cards produced by Tecmar/Scientific Solutions Inc. In 1981 IBM introduced the IBM Personal Computer and Scientific Solutions introduced the first PC data acquisition products. METHODOLOGYSources and systems: Data acquisition begins with the physical phenomenon or physical property to be measured. Examples of this include temperature, light intensity, gas pressure, fluid flow, and force. Regardless of the type of physical property to be measured, the physical state that is to be measured must first be transformed into a unified form that can be sampled by a data acquisition system. The task of performing such transformations falls on devices called sensors. A data acquisition system is a collection of software and hardware that lets you measure or control physical characteristics of something in the real world. A complete data acquisition system consists of DAQ hardware, sensors and actuators, signal conditioning hardware, and a computer running DAQ software.

A sensor, which is a type of transducer, is a device that converts a physical property into a corresponding electrical signal (e.g., strain gauge, thermistor). An acquisition system to measure different properties depends on the sensors that are suited to detect those properties. Signal conditioning may be necessary if the signal from the transducer is not suitable for the DAQ hardware being used. The signal may need to be filtered or amplified in most cases. Various other examples of signal conditioning might be bridge completion, providing current or voltage excitation to the sensor, isolation, linearization. For transmission purposes, single ended analog signals, which are more susceptible to noise can be converted to differential signals. Once digitized, the signal can be encoded to reduce and correct transmission errors.

DAQ hardware

DAQ hardware is what usually interfaces between the signal and a PC.[6] It could be in the form of modules that can be connected to the computer's ports (parallel, serial, USB, etc.) or cards connected to slots (S-100 bus, AppleBus, ISA, MCA, PCI, PCI-E, etc.) in the motherboard. Usually the space on the back of a PCI card is too small for all the connections needed, so an external breakout box is required. The cable between this box and the PC can be expensive due to the many wires, and the required shielding. DAQ cards often contain multiple components (multiplexer, ADC, DAC, TTL-IO, high speed timers, RAM). These are accessible via a bus by a microcontroller, which can run small programs. A controller is more flexible than a hard wired logic, yet cheaper than a CPU so that it is permissible to block it with simple polling loops. For example: Waiting for a trigger, starting the ADC, looking up the time, waiting for the ADC to finish, move value to RAM, switch multiplexer, get TTL input, let DAC proceed with voltage ramp. DAQ Device Drivers DAQ device drivers are needed in order for the DAQ hardware to work with a PC. The device driver performs low-level register writes and reads on the hardware, while exposing API for developing user applications in a variety of programming environments.

Input devices 3D scanner Analog-to-digital converter Time-to-digital converter Hardware[edit] Computer Automated Measurement and Control (CAMAC) Industrial Ethernet Industrial USB LAN eXtensions for Instrumentation NIM PowerLab PCI eXtensions for Instrumentation VMEbus

VXI

DAQ software Specialized DAQ software may be delivered with the DAQ hardware. Software tools used for building large-scale data acquisition systems include EPICS. Other programming environments that are used to build DAQ applications include ladder logic, Visual C++, Visual Basic, LabVIEW, and MATLAB. See also: LabChart MIDAS