CHAPTER 1

REVIEW OF COMPUTERS IN PROCESS CONTROL

1.1 DATA LOGGERS

1.1.1 Introduction

A data logger is an electronic device that records data over time or in relation to location either with a built in instrument or sensor or via external instruments and sensors. They generally are small, battery powered, portable, and equipped with a microprocessor, internal memory for data storage, and sensors. Electronic data loggers have replaced the chart recorder in many applications.

The data can be temperature, pressure, force, weather factors, humidity, voltage, current, resistance, strain, flow, displacement. This includes varied range of acquisition devices such as plug-in boards, or serial communication for recording of information on computer for real time recording. These are available in different size according to their function of the measurement. The main advantage of Data Loggers is that they can operate independently of a computer, unlike many other types of data acquisition devices. 

The Data logger is a standalone small, portable, battery operated device with a small LCD screen, while data acquisition system is concerned with direct interface with a computer or digital processor and also have a microprocessor system. More specifically, we can say the Data Loggers that can be integrated with industrial systems and alarms make remote monitoring relatively an easy task. Data logging is used in a broad spectrum of applications. It has extended its applications in the medical field also in order to measure PH, temperature and pressure in the laboratory during an experiment and research. Civil engineers use it to measure strain and load on buildings and bridges for safety purpose. Design engineers use to measure voltage, battery level, vibration, current, resistance, flow level and many more applications. The range of data loggers includes simple, economical single channel fixed function loggers to more powerful programmable devices capable of handling hundreds of inputs.

Figure 1.1 Block Diagram of Data Logger

A Data logger for recording the data involves the following processes:

Input Scanning Signal conditioning Analog to Digital Conversion Recording

1.1.2 Basic Assembly of Data Loggers

The basic assembly of data loggers consists of main frames, front panel assembly and Power supply with the following essential modules.

Scanner controller It acts as an interface between the logger and scanner.

Data exchange All data transfers within the logger is made through this module and it also ensures correct transmission of data.

Processor It controls the sequence of events within the logger by defining and producing commands for the modules.

Programmer It is used to setup the channel programs

Digital Voltmeter(DVM) interface The DVM functions like range, mode, integration periods, etc are selected by the program instruction and transmitted through the interface.

1.1.3 Characteristics and Selection Factor of Data Loggers

Type of Input Signal Number of Inputs Size Speed/Memory Real Time Operation

1.1.4 Types of Data Loggers

Data loggers can be of the following four types

Miniature Single Input Data Loggers Fixed Mount Multi-Channel Data Loggers Handheld Multi-Channel Data Loggers Modular Data Loggers

Miniature Single Input Data Loggers

Miniature single input data loggers are generally low cost loggers dedicated to a specific input type. These types of data loggers are often used in the transportation industry. A typical application would be to include a temperature data logger in a shipment of food products to insure that the food temperature does not exceed acceptable limits.

Fixed Mount Multi-Channel Data Loggers

Fixed input loggers have a fixed number of input channels which are generally dedicated to a specific type of input, they range from 1 to 8 channels.

Handheld Multi-Channel Data Loggers

Handheld multi-channel loggers are commonly used in applications where the data logger is to be carried from one location to another. They are also commonly used in bench top or laboratory environments. In addition to storing data internally, some models even contain on board printers which can produce an immediate hard copy of the data.

Modular Data Loggers

A modular data logger is configurable and expandable through the use of plug-in modules. The modules are normally field configurable and the user has the option of adding as many channels to satisfy the application requirement.

Consider the following typical data logger features versus its data acquisition:

Data loggers were battery powered. Data loggers were higher resolution devices.

Data loggers recorded to their own memory.

Data loggers operated at very less sample rates.

These distinctions have blurred over the last twenty years or so due mainly to technology advancements. For example, there used to be a huge cost difference between high speed and low speed, as well as high and low resolution analog to digital converters. Today, those differences have nearly been erased. A manufacturer can choose a high speed, high resolution and low power solution and deploy it as either a data logger or data acquisition solution at its discretion. Furthermore, much greater levels of integrated circuit density and functionality have allowed previously complex designs to be reduced to only a handful of ICs. From a firmware perspective, open source stacks that offer turnkey support for SD memory cards, Ethernet, WiFi, etc. may be implemented on nearly a whim by the manufacturer because of minimal development time and expense.

1.1.5 Data Loggers Vs Recorders

A data logger is an attractive alternative to either a recorder or data acquisition system in many applications. When compared to a recorder, data loggers have the ability to accept a greater number of input channels, with better resolution and accuracy. Also, data loggers usually have some form of on-board intelligence, which provides the user with diverse capabilities. For example, raw data can be analyzed to give flow rates, differential temperatures, and other interpreted data that otherwise would require manual analysis by the operator. The major difference between a data logger and a recorder, however, is the way the data itself is stored, analyzed and recorded. A common recorder accepts an input, and compares it to a full scale value. The pen arm is then deflected across the recording width, to produce the appropriate ratio of the actual input to the full scale input. For example, using a recorder with a 1 Volt full scale, an input of 0.5 Volts would move the pen 0.5/1 or 50% of the distance across the recording width. In comparison, a data logger accepts an input which is fed into an analog-to-digital converter prior to analysis and storage. This method has advantages in accuracy and resolution, while only a recorder can provide a truly continuous trend recording

1.1.6 Advantages

One of the primary benefits of using data loggers is the ability to automatically collect data on a 24-hour basis

This allows for a comprehensive, accurate picture of the environmental conditions being monitored such as air temperature and relative humidity

Slower sample rates Ease in use

1.1.7 Applications

Flight data recorder Process monitoring for maintenance and troubleshooting applications.  Monitoring of relay status in railway signalling. Unattended gas pressure recording. Tank level monitoring

1.2 DATA ACQUISITION

1.2.1 Introduction

In 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.

Data 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 with the acronym DAS or DAQ) typically convert analog waveforms into digital values for processing. The components of data acquisition systems include:

Sensors that convert physical parameters to electrical signals. Signal conditioning circuitry to convert sensor signals into a form that can be converted

to digital values. Analog-to-digital converters, which convert conditioned sensor signals to digital values.

Data acquisition applications are controlled by software programs developed using various general purpose programming languages such as BASIC, C, Fortran, Java, Lisp, Pascal.

1.2.2 Components of a Typical DAS

Figure 1.2 Components of a Typical DAS

Source

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 and Transducers.

A sensor is a device which senses or detects any change in physical property. A Transducer which has a sensor in built 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 the 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. 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 many wires, and the required shielding.

Figure 1.3 DAQ Hardware

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.

DAQ software

DAQ software is 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 a standard API for developing user applications. A standard API such as COMEDI allows the same user applications to run on different operating systems. For example, a user application that runs on Windows will also run on Linux.

Input devices

3D scanner A 3D scanner is a device that analyzes a real-world object or environment to collect data on its shape and possibly its appearance (i.e. color). The collected data can then be used to construct digital, three dimensional models.

Analog to digital converter An analog-to-digital converter (ADC) is a device that converts a continuous physical quantity (usually voltage) to a digital number that represents the quantity's amplitude.

Time to digital converter A time to digital converter (TDC) is a device for recognizing events and providing a digital representation of the time they occurred.

1.2.3 Selection Factors of ADC

The following are the important factors to be considered while selecting an ADC. They are

Resolution Speed of Conversion Cost Flexibility Performance Scalability

1.2.4 Data Loggers Vs Data Acquisition

Data Logging Data Acquisition

Data loggers typically have slower sample rates

Data acquisition has faster sample rates.

Data loggers are implicitly stand-alone devices Data acquisition system must remain tethered to a computer to acquire data

Recorded data value is associated with a date and time of acquisition in order to produce a sequence of events using real-time clock (RTC).

Real-Time Clock (RTC) not required.

Table 1.1 Difference between Data Logging and Data Acquisition

1.3 SAMPLING CONSIDERATIONS

In signal processing, sampling can be described as the process by which analog signals are converted into discrete signals. There are a large number of applications for sampling, falling under the two categories: Audio sampling and video sampling.

A sampler is a subsystem or operation that extracts samples from a continuous signal. A theoretical ideal sampler produces samples equivalent to the instantaneous value of the continuous signal at the desired points.

The sampling rate, sample rate, or sampling frequency ( ) defines the number of samples per unit of time (usually seconds) taken from a continuous signal to make a discrete signal. For time-domain signals, the unit for sampling rate is hertz (inverse seconds, 1/s, s−1). The inverse of the sampling frequency is the sampling period or sampling interval, which is the time between samples.

Figure 1.4 Analog signal (light blue) with a sampled signal (red) with a fixed spacing or sampling rate

1.3.1 Sampling theorem

The Nyquist–Shannon sampling theorem states that perfect reconstruction of a signal is possible when the sampling frequency is greater than twice the maximum frequency of the signal being sampled.The Nyquist sampling theorem provides a prescription for the nominal sampling interval required to avoid aliasing.

It may be stated simply as follows:

The sampling frequency should be at least twice the highest frequency contained in the signal.or in mathematical terms:

Fs > 2 fm

where fs is the sampling frequency (how often samples are taken per unit of time or space), and fm is the highest frequency contained in the signal. If lower sampling rates are used, the original signal's information may not be completely recoverable from the sampled signal.

The full range of human hearing is between 20 Hz and 20 kHz. The minimum sampling rate that satisfies the sampling theorem for this full bandwidth is 40 kHz. The sampling rate of 44.1 kHz is used for Compact Disc.

1.3.2 Optimums Sampling Period

The selection of sampling rate is of prime importance when sampling is to be done on signals such as medical signals (ECG and EEG).

In Signal Processing, there are two techniques used for sampling which are as follows:

Oversampling

Oversampling is the process of sampling a signal with a sampling frequency significantly higher than twice the bandwidth or highest frequency of the signal being sampled. Oversampling helps avoid aliasing, improves resolution and reduces noise.

Undersampling

Undersampling or Bandpass sampling is a technique where one samples a bandpass-filtered signal at a sample rate below its Nyquist rate (twice the upper cut-off frequency), but is still able to reconstruct the signal. For a baseband signal (one that has components from 0 to the band limit), such sampling introduces aliasing.

Selection of Optimum sampling period

The simplest method for selecting the sampling period is the one recommended in the DDC guidelines established by the 1963 Users Conference. These guidelines recommended the sampling period for few general processes as follows:

Flow loops --1 second Level loops -- 5 seconds Pressure Loops -- 5 seconds Temperature Loops -- 20 seconds

The designer should ensure that the sampling period selected is as large as possible, consistent with good control.

When a digital computer is used to execute the PID control equations, there exists a lower limit on the sampling period, because if T is too small, a reset deadband may result when a fixed point calculation is used to implement the control algorithm. The lower limit on sampling period for

the PID control is: ; where is Integral time.

1.4 SUPERVISORY CONTROL AND DATA ACQUISTION SYSTEMS

1.4.1 Introduction

SCADA is an acronym for Supervisory Control and Data Acquisition, which is a computer system for gathering and analyzing real-time data. Such systems were first used in the 1960s. The SCADA industry was essentially born out of a need for a user friendly front-end to a control system containing PLCs (programmable logic controllers). SCADA systems are used to monitor and control a plant or equipment in industries such as telecommunications, water and waste control, energy, oil and gas refining and transportation. One of the key processes of SCADA is the ability to monitor an entire system in real time. This is facilitated by data acquisitions including meter reading and checking statuses of sensors that are communicated at standard intervals depending on the system.

SCADA can also be seen as a system with many data elements called points. Each point is a monitor or sensor and these points can be either hard or soft. A hard data point can be an actual monitor; a soft point can be viewed upon as an application or software calculation. Data elements from hard and soft points are usually always recorded and logged to create a time stamp or history. SCADA can come in open and non-proprietary protocols. Smaller systems are extremely affordable and can either be purchased as a complete system or can be mixed and matched with specific components. Large systems can also be created with off-the-shelf components. SCADA system software can also be easily configured for almost any application, removing the need for custom software development.

These systems encompass the transfer of data between a SCADA central host computer and a number of Remote Terminal Units (RTUs) and/or Programmable Logic Controllers (PLCs), and the central host and the operator terminals. A SCADA system gathers information (such as where a leak on a pipeline has occurred), transfers the information back to a central site, then alerts the home station that a leak has occurred, carrying out necessary analysis and control, such as determining if the leak is critical, and displaying the information in a logical and organized fashion. These systems can be relatively simple, such as one that monitors environmental conditions of a small office building, or very complex, such as a system that monitors all the activity in a nuclear power plant or the activity of a municipal water system. Traditionally, SCADA systems have made use of the Public Switched Network (PSN) for monitoring purposes. Today many systems are monitored using the infrastructure of the corporate Local Area Network (LAN)/Wide Area Network (WAN). Wireless technologies are now being widely deployed for purposes of monitoring.

1.4.2 Elements of SCADA system A SCADA system consists of:

One or more field data interface devices, usually RTUs, or PLCs, which interface to field sensing devices and local control switchboxes and valve actuators

A communications system used to transfer data between field data interface devices and control units and the computers in the SCADA central host. The system can be radio, telephone, cable, satellite, etc., or any combination of these.

A central host computer server or servers (sometimes called a SCADA Center, master station, or Master Terminal Unit (MTU)

A collection of standard and/or custom software [sometimes called Human Machine Interface (HMI) software or Man Machine Interface (MMI) software] systems used to provide the SCADA central host and operator terminal application, support the communications system, and monitor and control remotely located field data interface devices

Figure 1.5 Typical SCADA system

Field Data Interface Devices

Field data interface devices form the "eyes and ears" of a SCADA system. Devices suchas reservoir level meters, water flow meters, valve position transmitters, temperature transmitters, power consumption meters, and pressure meters all provide information that can tell an experienced operator how well a water distribution system is performing. In addition, equipment such as electric valve actuators, motor control switchboards, and electronic chemical dosing facilities can be used to form the "hands" of the SCADA system and assist in automating the process of distributing water.However, before any automation or remote monitoring can be achieved, the information that is passed to and from the field data interface devices must be converted to a form that is compatible with the language of the SCADA system. To achieve this, some form of electronic field data interface is required. RTUs, also known as Remote Telemetry Units, provide this interface. They are primarily used to convert electronic signals received from field interface devices into the language (known as the communication protocol) used to transmit the data over a communication channel.

Communications Network

The communications network is intended to provide the means by which data can be transferred between the central host computer servers and the field-based RTUs. The Communication Network refers to the equipment needed to transfer data to and from different sites. The medium used can either be cable, telephone or radio.The use of cable is usually implemented in a factory. This is not practical for systems covering large geographical areas because of the high cost of the cables, conduits and the extensive labour in installing them. The use of telephone lines (i.e., leased or dial-up) is a more economical solution for systems with large coverage. The leased line is used for systems requiring on-line connection with the remote stations. Dial-up lines can be used on systems requiring updates at regular intervals (e.g., hourly updates). Here ordinary telephone lines can be used. The host can dial a particular number of a remote site to get the readings and send commands.

Remote sites are usually not accessible by telephone lines. The use of radio offers an economical solution. Radio modems are used to connect the remote sites to the host. An on-line operation can also be implemented on the radio system. For locations where a direct radio link cannot be established, a radio repeater is used to link these sites. Historically, SCADA networks have been dedicated networks; however, with the increased deployment of office LANs and WANs as a solution for interoffice computer networking, there exists the possibility to integrate SCADA LANs into everyday office computer networks.

Central Host Computer

The central host computer or master station is most often a single computer or a networkof computer servers that provide a man-machine operator interface to the SCADA system. The computers process the information received from and sent to the RTU sites and present it to human operators in a form that the operators can work with. Operator terminals are connected to the central host computer by a LAN/WAN so that the viewing screens and associated data can be displayed for the operators. Recent SCADA systems are able to offer high resolution computer graphics to display a graphical user interface or mimic screen of the site. Historically, SCADA

vendors offered proprietary hardware, operating systems, and software that was largely incompatible with other vendors' SCADA systems. Expanding the system required a further contract with the original SCADA vendor. Host computer platforms characteristically employed UNIX-based architecture..However, with the increased use of the personal computer, computer networking has become commonplace in the office and as a result, SCADA systems are now available that can network with office-based personal computers. Indeed, many of today's SCADA systems can reside on computer servers that are identical to those servers and computers used for traditional office applications. This has opened a range of possibilities for the linking of SCADA systems to office-based applications such as GIS systems, hydraulic modeling software, drawing management systems, work scheduling systems, and information databases.

Operator Workstations and Software Components

Operator workstations are most often computer terminals that are networked with the SCADA central host computer. The central host computer acts as a server for the SCADA application, and the operator terminals are clients that request and send information to the central host computer based on the request and action of the operators.

An important aspect of every SCADA system is the computer software used within the system. The most obvious software component is the operator interface or Man Machine Interface/Human Machine Interface (MMI/HMI) package; however, software of some form pervades all levels of a SCADA system. Depending on the size and nature of the SCADA application, software can be a significant cost item when developing, maintaining, and expanding a SCADA system. When software is well defined, designed, written, checked, and tested, a successful SCADA system will likely be produced. Poor performances in any of these project phases will very easily cause a SCADA project to fail.

Many SCADA systems employ commercial proprietary software upon which the SCADA system is developed. The proprietary software often is configured for a specific hardware platform and may not interface with the software or hardware produced by competing vendors. It is therefore important to ensure that adequate planning is undertaken to select the software systems appropriate to any new SCADA system.

1.4.3 SCADA Architectures

SCADA systems have evolved in parallel with the growth and sophistication of moderncomputing technology. The following sections will provide a description of the following three generations of SCADA systems:

First Generation – Monolithic Second Generation – Distributed Third Generation – Networked

Monolithic SCADA Systems

When SCADA systems were first developed, the concept of computing in general centered on “mainframe” systems. Networks were generally non-existent, and each centralized system stood alone. As a result, SCADA systems were standalone systems with virtually no connectivity to other systems. The Wide Area Networks (WANs) that were implemented to communicate with remote terminal units (RTUs) were designed with a single purpose in mind–that of communicating with RTUs in the field and nothing else. In addition, WAN protocols in use today were largely unknown at the time. The communication protocols in use on SCADA networks were developed by vendors of RTU equipment and were often proprietary.

Redundancy in these first generation systems was accomplished by the use of two identically equipped mainframe systems, a primary and a backup, connected at the bus level. The standby system’s primary function was to monitor the primary and take over in the event of a detected failure. This type of standby operation meant that little or no processing was done on the standby system..

Figure 1.6 First Generation SCADA Architecture

Distributed SCADA Systems

The next generation of SCADA systems took advantage of developments and improvement in system miniaturization and Local Area Networking (LAN) technology to distribute the processing across multiple systems. Multiple stations, each with a specific function, were connected to a LAN and shared information with each other in real-time. These stations were typically of the mini-computer class, smaller and less expensive than their first generation processors.

Some of these distributed stations served as communications processors, primarily communicating with field devices such as RTUs. Some served as operator interfaces, providing

the human-machine interface (HMI) for system operators. Still others served as calculation processors or database servers. The distribution of individual SCADA system functions across multiple systems provided more processing power for the system as a whole than would have been available in a single processor. The networks that connected these individual systems were generally based on LAN protocols and were not capable of reaching beyond the limits of the local environment.

Distribution of system functionality across network-connected systems served not only to increase processing power, but also to improve the redundancy and reliability of the system as a whole. Rather than the simple primary/standby failover scheme that was utilized in many first generation systems, the distributed architecture often kept all stations on the LAN in an online state all of the time. For example, if an HMI station were to fail, another HMI station could be used to operate the system, without waiting for failover from the primary system to the secondary.

eFigure 1.7 Second Generation SCADA Architecture

Networked SCADA Systems

The current generation of SCADA master station architecture is closely related to that ofthe second generation, with the primary difference being that of an open system architecture rather than a vendor controlled, proprietary environment. The major improvement in the thirdgeneration is that of opening the system architecture, utilizing open standards and protocols and making it possible to distribute SCADA functionality across a WAN and not just a LAN. Open standards eliminate a number of the limitations of previous generations of SCADA systems. The utilization of off-the-shelf systems makes it easier for the user to connect third party peripheral

devices (such as monitors, printers, disk drives, tape drives, etc.) to the system and/or the network.

As they have moved to “open” or “off-the-shelf” systems, SCADA vendors have gradually got out of the hardware development business. These vendors have looked to system vendors for their expertise in developing the basic computer platforms and operating system software. This allows SCADA vendors to concentrate their development in an area where they can add specific value to the system–that of SCADA master station software.

The major improvement in third generation SCADA systems comes from the use of WAN protocols such as the Internet Protocol (IP) for communication between the master station and communications equipment.

Figure 1.8 Third Generation SCADA Architecture

1.4.4 Functions performed by a SCADA system

A SCADA system performs four functions:

1. Data acquisition2. Networked data communication3. Data presentation4. Control

These functions are performed by several kinds of SCADA components:

Sensors (either digital or analog) and control relays that directly interface with the managed system.

Remote telemetry units (RTUs). These are small-computerized units deployed in the field at specific sites and locations. RTUs serve as local collection points for gathering reports from sensors and delivering commands to control relays.

SCADA master units. These are larger computer consoles that serve as the central processor for the SCADA system. Master units provide a human interface to the system and automatically regulate the managed system in response to sensor inputs.

The communications network that connects the SCADA master unit to the RTUs in the field monitor at the remote sites.

Data Acquisition

First, the systems you need to monitor are much more complex than just one machine with one output. So a real-life SCADA system needs to monitor hundreds or thousands of sensors. Some sensors measure inputs into the system (for example, water flowing into a reservoir), and some sensors measure outputs (like valve pressure as water is released from the reservoir). Some of those sensors measure simple events that can be detected by a straightforward on/off switch, called a discrete input (or digital input).

Data Communication Real SCADA systems don’t communicate with just simple electrical signals, either. SCADA data is encoded in protocol format. Older SCADA systems depended on closed proprietary protocols, but today the trend is to open, standard protocols and protocol mediation. Sensors and control relays are very simple electric devices that can’t generate or interpret protocol communication on their own. Therefore the remote telemetry unit (RTU) is needed to provide an interface between the sensors and the SCADA network. The RTU encodes sensor inputs into protocol format and forwards them to the SCADA master; in turn, the RTU receives control commands in protocol format from the master and transmits electrical signals to the appropriate control relays.

Data PresentationThe only display element in our model SCADA system is the light that comes on when

the switch is activated. A real SCADA system reports to human operators over a specialized computer that is variously called a master station, an HMI (Human-Machine Interface) or an HCI (Human-Computer Interface).

The SCADA master station has several different functions. The master continuously monitors all sensors and alerts the operator when there is an “alarm” — that is, when a control factor is operating outside what is defined as its normal operation. The master presents a comprehensive view of the entire managed system, and presents more detail in response to user requests. The master also performs data processing on information gathered from sensors. It maintains report logs and summarizes historical trends. An advanced SCADA master can add a great deal of intelligence and automation to the systems management.

Control

In real life, SCADA systems automatically regulate all kinds of industrial processes. For example, if too much pressure is building up in a gas pipeline, the SCADA system can automatically open a release valve. Electricity production can be adjusted to meet demands on the power grid. Even these real world examples are simplified; a full-scale SCADA system can adjust the managed system in response to multiple inputs.

1.4.5 SCADA SECURITYThere are two types of process-control systems in view—distributed control systems

(DCS) and supervisory control and acquisition (SCADA). DCS are typically used for single-point processing and are employed in a limited geographic area. On the other hand, SCADA systems are used for large scale, distributed management of critical infrastructure systems and are often geographically dispersed.

Figure 1.9 Process Control SystemFor example, in a power utility, DCS may be used for generation of power, while SCADA is used for the distribution and transmission of power. The basic SCADA configuration shown in Figure, consists of a supervisory control station and multiple controller stations, either local or remote. Through the use of the control station, operators can monitor status and issue commands to the appropriate devices. Control stations consist of devices that collect data or effect control of equipment. These devices are either remote terminal units (RTU), intelligent electronic devices or programmable logic controllers.

1.4.6 POTENTIAL BENEFITS OF SCADA

Reliability and robustness: These systems are used for mission critical industrial processes where reliability and performance are paramount. In addition, specific development is performed within a well-established framework that enhances reliability and robustness.Maximize productivity: Maximizes productivity and ensures continuous production. SCADA's design is centered on multi-level redundancy to ensure constant communication and operation of your system.

Improve product quality: Analyzes and controls the quality of manufactured products using standard SCADA functionality, such as Statistical Process Control (SPC). Advanced statistical alarms enable your personnel to perform predictive calibration of process parameters, thus preventing out of limit deviations before they occur.Reduce your operating and maintenance costs: Through the deployment of a centralized SCADA system you can significantly reduce operating and maintenance costs; fewer personnel are required to monitor field equipment in remote locations, resulting in increased operational effectiveness; and less maintenance trips are required, resulting in decreased maintenance and training costs.Integrate with your business systems: A SCADA system can be easily integrated with your existing business systems, leading to increased production and profitability. In addition, this system implementation allows you to transform, analyze and present real-time information throughout the enterprise for prioritized decision-making.Preserve your capital investment: When you spend money to improve operations, you need to ensure prolonged use; SCADA's open system design protects against control system obsolescence and can be easily scaled to meet growing demands of operations.

1.4.7 Applications of SCADA

SCADA can be used to manage many kinds of equipment. Typically, SCADA systems are used to automate complex industrial processes where human control is impractical. Around the world, SCADA system controls are used in the following industries:

Manufacturing: SCADA systems manage parts inventories for JIT manufacturing, regulate industrial automation and robots, and monitor process and quality control.Buildings, facilities and environments: Facility managers use SCADA to control HVAC, refrigeration units, lighting and entry systems.Electric power generation, transmission and distribution: Electric utilities use SCADA systems to detect current flow and line voltage, to monitor the operation of circuit breakers, and to take sections of the power grid online or offline.Water and sewage: State and municipal water utilities use SCADA to monitor and regulate water flow, reservoir levels, and pipe pressure.Mass transit: Transit authorities use SCADA to regulate electricity to subways, trams and trolley buses; to automate traffic signals for rail systems; to track and locate trains and buses; and to control railroad-crossing gates.Traffic signals: SCADA regulates traffic lights, controls traffic flow and detects out-of-order signals.

1.5 COMPUTER CONTROL SYSTEM

1.5.1 Functional Block Diagram of Computer Control System

Now a day’s most of the industrial control is done using computers. Every control system incorporated into the industry is a computer based control system or simply a computer control system.

The general block diagram of a computer control system is given by:

Set point

Figure 1.5 Block Diagram of a Computer Control System

1.5.2 Analog to Digital Converter

Figure 1.6 Mechanism of ADC

Analog to digital converters are employed in industry to convert the signals obtained from the transmitters (e.g. pressure and temperature) into digital signals for the processing of signals.

The heart of the computer based data acquisition is usually the analog to digital converter. Basically this device is a voltmeter. Its input is voltage and its output is a digital number proportional to the input voltage. The computer is usually programmed to convert this outputted digital number into a number that represents the measured voltage.

There are a wide variety of ADC’s. They are of different ranges and various bit ranges. It generally varies between 4 bit to 16 bit ADC’s.

Figure 1.7 Types of ADC’s and their Comparison

1.5.3 Types of Analog to Digital Converter

ADC Controller equation

DAC Control Valve

Measured Variable

Process

The most common types of ADC’s are as follows:

Flash type ADC

Figure 1.8 Flash type ADC

A direct-conversion ADC or flash ADC has a bank of comparators sampling the input signal in parallel, each firing of their decoded voltage range. The comparator bank feeds a logic circuit that generates a code for each voltage range. Direct conversion is very fast, capable of gigahertz sampling rates, but usually has only 8 bits of resolution or less, since the number of comparators needed, 2N - 1, doubles with each additional bit, requiring a large, expensive circuit. ADCs of this type have a large die size, a high input capacitance, high power dissipation, and are prone to produce glitches at the output (by outputting an out-of-sequence code. They are often used for video, wideband communications or other fast signals in optical storage.

Successive-Approximation type ADC

Figure 1.9 Successive Approximation Register Type

A successive-approximation ADC uses a comparator to successively narrow a range that contains the input voltage. At each successive step, the converter compares the input voltage to the output of an internal digital to analog converter which might represent the midpoint of a selected voltage range. At each step in this process, the approximation is stored in a successive approximation register (SAR). For example, consider an input voltage of 6.3 V and the initial range is 0 to 16 V. For the first step, the input 6.3 V is compared to 8 V (the midpoint of the 0–16 V range). The comparator reports that the input voltage is less than 8 V, so the SAR is updated to narrow the range to 0–8 V. For the second step, the input voltage is compared to 4 V (midpoint of 0–8). The comparator reports the input voltage is above 4 V, so the SAR is updated to reflect the input voltage is in the range 4–8 V. For the third step, the input voltage is compared with 6 V (halfway between 4 V and 8 V); the comparator reports the input voltage is greater than 6 volts, and search range becomes 6–8 V. The steps are continued until the desired resolution is reached.

Ramp-Compare ADC

Figure 1.10 Ramp-Compare type

A ramp-compare ADC produces a saw-tooth signal that ramps up or down then quickly returns to zero. When the ramp starts, a timer starts counting.The output of a binary counter is connected to a DAC which produces a ramp wave. A comparator is used to compare the ramp with the signal to be converted. When the comparator changes state, the binary data is latched. In this way the analogue input is converted to binary numbers. The ramp time is sensitive to temperature because the circuit generating the ramp is often just some simple oscillator. There

are two solutions: use a clocked counter driving a DAC and then use the comparator to preserve the counter's value, or calibrate the timed ramp. A special advantage of the ramp-compare system is that comparing a second signal just requires another comparator, and another register to store the voltage value. This type of ADC is fairly slow (but cheap and simple) and it is ideal for data that changes fairly slowly such as vehicle or aircraft control systems.

Integrating ADC

Figure 1.11 Integrating type

An integrating ADC (also dual-slope or multi-slope ADC) applies the unknown input voltage to the input of an integrator. A current, proportional to the input voltage, charges a capacitor for a fixed time interval T .  At the end of this interval, the device resets its counter and applies an opposite-polarity negative reference voltage to the integrator input.  Because of this, the capacitor is discharged by a constant current until the integrator output voltage zero again. The T discharge interval is proportional to the input voltage level and the resultant final count provides the digital output, corresponding to the input signal.  This type of ADC is extremely slow devices with low input bandwidths. The speed of the converter can be improved by sacrificing resolution. Their advantage, however, is their ability to reject high-frequency noise and AC line noise such as 50Hz or 60Hz which makes them useful in noisy industrial environments. Such types are used in most digital voltmeters for their linearity and flexibility.

1-5.3 Digital to Analog Converter

A digital-to-analog converter (DAC or D-to-A) is a device for converting a digital (usually binary) code to an analog signal (current, voltage or electric charge). Signals are easily stored and transmitted in digital form, but a DAC is needed for the signal to be recognized by human senses or other non-digital systems. So DAC tends to be the interface between the abstract digital world and the analog real life. Simple switches, a network of resistors, current sources or capacitors may implement this conversion. A DAC inputs a binary number and outputs an analog voltage or current signal.

Figure 1.12 DAC Mechanism

The most common types of DAC’s are as follows:

Binary-Weighted Resistor DAC

Figure 1.13 Binary-Weighted Resistor type

The binary-weighted-resistor DAC employs the characteristics of  the inverting summer Op Amp circuit.  In this type of DAC, the output voltage is the inverted sum of all the input voltages. If the input resistor values are set to multiples of two: 1R, 2R and 4R, the output voltage would be equal to the sum of V1, V2/2 and V3/4.

Vout = - (V1 + V2/2 + V3/ 4)

where V1 corresponds to the most significant bit (MSB) while V3 corresponds to the least significant bit (LSB).This is one of the fastest conversion methods, but suffers from poor accuracy because of the high precision required for each individual voltage or current. Such high-precision resistors and current sources are expensive, so this type of converter is usually limited to 8-bit resolution or less.

R-2R Ladder DAC

Figure 1.14 R-2R Ladder type

An enhancement of the binary-weighted resistor DAC is the R-2R ladder network. This type of DAC utilizes Thevenin’s theorem in arriving at the desired output voltages. The R-2R network consists of resistors with only two values - R and 2R.  If each input is supplied either 0 volts or reference voltage, the output voltage will be an analog equivalent of the binary value of the three bits. This improves DAC precision due to the ease of producing many equal matched values of resistors or current sources, but lowers conversion speed due to parasitic capacitance.

Vout =   - (VMSB + Vn + VLSB)

Vout = - (VRef + VRef/2 + VRef/ 4)

where VMSB corresponds to the most significant bit (MSB) and VLSB corresponds to the least significant bit (LSB).

Pulse Width Modulator

A basic form of digital to analog conversion is Pulse Width Modulation (PWM).It is the simplest DAC type. It is a process that involves the transmission of analog information over a series of pulses. The transmitted data are encoded in the width of these pulses resulting to corresponding digital signals. The resultant variable width pulses represent the amplitude of an input analog signal. The reverse process is done in converting the PWM generated digital signal to analog. Typical application is in power and voltage regulation. This technique is often used for electric motor speed control.

Delta-Sigma DAC

Oversampling DACs such as the delta-sigma DAC use a pulse density conversion technique. The oversampling technique allows for the use of a lower resolution DAC internally. A simple 1-bit DAC is often chosen, as it is inherently linear. The DAC is driven with a pulse-density modulated signal, created with the use of a low-pass filter, step nonlinearity and negative feedback loop, in a technique called delta-sigma modulation. This results in an effective high-pass filter acting on the quantization noise. Most very high resolution DACs (greater than 16 bits) are of this type due to its high linearity and low cost. Speeds of greater than 100 thousand samples per second and resolutions of 24 bits are attainable with delta-sigma DACs.

Thermometer Coded DAC

Thermometer Coded DAC employs a number of equally weighted elements that contains an equal resistor segment for each possible value of DAC output. This is currently the fastest and highest precision DAC architecture available, but the trade-off is high cost.  This type of DAC requires very high sampling rates with achieving speeds of more than 1 billion samples per second.

Hybrid DAC

Hybrid DACs use a combination of the above techniques plus either that of the binary-weighted or ladder type of DAC. The objective is to achieve the characteristics of an ideal DAC – high speed, high precision and low cost. A good example is the Segmented DAC, which utilizes the thermometer coded principle for the MSBs and the binary weighted principle for the LSBs. This makes the Segmented DAC a practical and cost-effective solution.

1.6 DIRECT DIGITAL CONTROL

1.6.1 Introduction Direct digital control (DDC) is the automated control of a process by a digital device such as using the computer to perform the operation of a controller. Central controllers and most terminal unit controllers are programmable, meaning the direct digital control program code may be customized for the intended use. The program features include time schedules, set points, controllers, logic, timers, trend logs, and alarms. In DDC, the computer is used in the primary control loop itself.In this approach, process measurements are read by the computer directly, the computer calculates the proper control outputs, then sends the output directly to the actuation devices.

Direct digital control consists of enabling the computer (controller) to work in a feedback loop configuration as well as using, for instance, a three mode control algorithm(PID- Proportional+Integral+Derivative).It is of course allowed to use different control algorithms, however in 90% of the problems PID is sufficient. When DDC controllers are networked together they can share information through a data bus. The control system may speak 'proprietary' or 'open protocol' language to communicate on the data bus. Examples of open protocol language are BACnet (Building Automation Control Network), LON (Echelon), Modbus.

1.6.2 The Position Algorithm Position PID is the algorithm typically used to perform closed-loop control on a

position feedback axis. The Position PID provides very good control and is suitable for nearly all control systems. The Position PID works on a position feedback only and controls both position and velocity. The output of the position algorithm gives the new position of the final control element, in absolute term.

PID stands for the central gains used in this mode: Proportional, Integral, and Differential. The PID equation is generally represented by,

Yn= KP.en+ KD. + + Y0 (1.1)

WhereYn= valve position at time nY0= median valve position KP= proportional gain=100/PB (where, PB=proportional band in percent)KI=integral gainKD= derivative gainen= error at instant tn = (S-Vn)Vn= value of controlled variable at instant tn

S= set-pointThe PID controller control can be realized with a microprocessor based system, if only the above equation is implemented in the software. Apparently, it is very difficult to write the software for implementing the above equation for a microprocessor based system. However, the above equation can be modified such that its software implementation becomes easy. The modifications are discussed in the following section.

The integral term at any given instant tn is equal to the algebraic sum of all the control forces generated by the integral control action from the beginning to that instant.Thus the integral term can be represented as

and the differential term, KD. at any instant tn is proportional to the rate of change of the error.Thus, differential term, can be represented as

Where, en is the current error and en-1 is the previous error calculated at the instant tn-1. Thus, with these modifications the three-mode controller equation will become:

Yn= + + + Y0 (1.2)

The integral and the differential control forces are dependent upon the interval between two consecutive errors. This interval is the inverse of the rate at which the value of the controlled variable measured i.e, the sampling rate. Hence the provision for defining the sampling rate should be made available in the software.

The two modifications that can be performed on above equations are Trapezoidal rule for integral term and interpolation technique for derivative term.

Trapezoidal rule for integral termThe integral term can be represented using trapezoidal rule:

(1.3)

This will give better accuracy than previous term,

based on rectangular rule.

Interpolation technique for derivative termThe first difference in the derivative term, (en-en-1) is affected by noise, and thus, differentiation is sensitive to data error and noise. The noise can be reduced by using analog or digital filters. However, the technique commonly used is an interpolation method with four-point control difference technique.

Let vn, vn-1, vn-2, and vn-3 be the values of the controlled variable at the current and the previous consecutive sampling intervals. V*= (vn+ vn-1+ vn-2 + vn-3)/4 (1.4)

= [(Vn-V*). + (Vn-1-V*). + (V*-Vn-2). + (V*-Vn-3). ]

= [Vn-V*+ 3Vn-1- 3V*- 3 Vn-2+V*- Vn-3]

= [Vn+ 3Vn-1- 3Vn-2- Vn-3] (1.5)

Since set-point is constant,

= = [en+ 3en-1- 3en-2- en-3] (1.6)

Thus, with the two modifications, the controller equation becomes

Yn= + [en+ 3en-1- 3en-2- en-3] + + Y0 (1.7)

The position algorithm has distinct properties that it maintains its own reference in Y0.

Position PID Advantages

Tracks position very well. Is very well understood by most people in the motion control industry.

Position PID Disadvantages

Lack of bumpless transfer from manual to auto switching Reset windup due to integral saturation in test mode

Tendency to overshoot final position on some systems.

1.6.3 The Velocity Algorithm

In number of control loops, the final control element is a stepper motor or stepper motor driven valve. In such cases, the requirement of the computer output will be a pulse train specifying the change in valve position. Thus the output of position algorithm cannot be used, since it gives the new position of the valve, in absolute term.

In velocity algorithm, the computer calculates the required change in valve position. The output is a digital pulse train which can be directly used in case valve is stepper motor driven. So the drawbacks faced by the position algorithm have been overcome in velocity type of the PID algorithm. The Eq. (1.2) of position algorithm derived earlier is

Yn= + + + Y0 (1.8)

Where Yn is the valve position at tn.At tn-1 i.e. at previous instant, the valve position was,

Yn-1= + + + Y0 (1.9)

The change in valve position at tn will thus be,

=

= + + (1.10)

The integral term and derivative term can be modified by using trapezoidal rule and interpolation technique similar to position algorithm.

Integral term =

= (1.11)

Derivative term = [(en+ 3en-1- 3en-2- en-3)-( en-1+ 3en-2- 3en-3- en-4)] =[en+2en-1- 6en-2+ 2en-3+ en-4] (1.12)

By substituting modified integral or differential terms in (10), we get

= +[en+2en-1- 6en-2+ 2en-3+ en-4] + (1.13)

The relationship between position and velocity algorithm is, Yn = Yn- Yn-1

i.e; Yn = Yn + Yn-1

= Yn + [ Yn-1+Yn-2] = Yn + Yn-1+[Yn-2+Yn-3]

Yn = +Y0

Logically also, the present valve position is equal to original position plus sum of all the changes occurred so far.

The velocity algorithm at equation (1.13) exhibits two measure problems: Controller drift

The velocity algorithm must contain the integral term else controller drift might arise. And the proportional term might give rise to oscillations. The oscillation problem can be solved by disregarding the sign of the proportional term and assigning the same sign as the integral term.

Integral overshootWhen the proportional term is forced to have the same sign as the integral term

the value of the controlled variable will reach the set point at a faster rate and overshoot it. It has been found that 7% of full scale set point band gives results on simulation tests of systems with first and second order time constants.