A distributed control system (DCS) is a control system used to control industrial processes in which control functions are distributed among multiple autonomous controllers like Programmable Logic Controller (PLC) connected by a communication network. These controllers are typically located near the process equipment or within plant control areas, while operator interfaces, supervisory control, alarm management, and process monitoring are commonly provided through centralised operator stations. This architecture contrasts with centralised control systems, in which control functions are performed primarily by a central controller or computer system. By distributing control functions across multiple controllers, a DCS can improve system availability, scalability, and fault isolation, while reducing the amount of dedicated point-to-point wiring required for large industrial processes.
DCS first emerged in large, high value, safety critical process industries, and were attractive because the DCS manufacturer would supply both the local control level and central supervisory equipment as an integrated package, thus reducing design integration risk. Today the functionality of supervisory control and data acquisition (SCADA) and DCS systems are very similar, but DCS tends to be used on large continuous process plants where high reliability and security is important, and the control room is not necessarily geographically remote. Many machine control systems exhibit similar properties as plant and process control systems do.
Structure
The key attribute of a DCS is its reliability due to the distribution of the control processing around nodes in the system. This mitigates a single processor failure. If a processor fails, it will only affect one section of the plant process, as opposed to a failure of a central computer which would affect the whole process. This distribution of computing power local to the field Input/Output (I/O) connection racks also ensures fast controller processing times by removing possible network and central processing delays.
The accompanying diagram is a general model which shows functional manufacturing levels using computerised control.
Referring to the diagram;
Level 0 contains the field devices such as flow and temperature sensors, and final control elements, such as control valves Level 1 contains the industrialised Input/Output (I/O) modules, and their associated distributed electronic processors. Level 2 contains the supervisory computers, which collect information from processor nodes on the system, and provide the operator control screens. Level 3 is the production control level, which does not directly control the process, but is concerned with monitoring production and monitoring targets Level 4 is the production scheduling level.
Levels 1 and 2 are the functional levels of a traditional DCS, in which all equipment are part of an integrated system from a single manufacturer.
Levels 3 and 4 are not strictly process control in the traditional sense, but where production control and scheduling takes place.
Technical points
The processor nodes and operator graphical user interfaces are connected over proprietary or industry-standard networks. Network reliability can be increased through redundant communication networks and diverse cable routes. This distributed topology can also reduce the amount of field cabling required by locating I/O modules and associated controllers closer to the process equipment.
The controllers receive information from input modules, process the information, and determine control actions that are transmitted through output modules. Field inputs and outputs can be analog signals, such as 4–20 mA DC current loops, or discrete signals that represent two states, such as "on" and "off". Discrete signals may be transmitted through relay contacts or semiconductor switching devices.
DCSs are connected to sensors and actuators and use setpoints and control algorithms to regulate industrial processes. A typical application is a PID controller that receives feedback from a flow meter and controls a control valve as the final control element. The controller compares the measured process variable with the required setpoint and adjusts the control valve to reduce the difference between them.
Large oil refineries and chemical plants can have several thousand I/O points and employ large DCSs. DCSs are also used in a wide range of other industrial processes, including paper machines and their associated quality-control systems, variable-speed drives, motor control centers, cement kilns, mining operations, and ore-processing facilities.
In high-reliability applications, DCSs may use redundant controllers, processors, communication networks, power supplies, and other system components. Redundant processors can be configured to support automatic failover, in which a standby processor assumes control if the primary processor fails. Some systems may also support manual switchover for maintenance or testing.
Although 4–20 mA signalling has historically been a widely used field signalling standard, modern DCSs also support digital communication protocols and networks, including fieldbus protocols such as Foundation Fieldbus and PROFIBUS, as well as protocols such as HART and Modbus.
Modern DCSs may also support advanced control techniques, including neural networks and fuzzy logic. Research in distributed control also includes the design of distributed controllers for spatially interconnected systems and the optimization of control performance according to criteria such as H-infinity and H2 control criteria.
Signal flow and termination In a typical DCS installation, signals from field instruments are connected to termination assemblies or marshalling cabinets before being routed to the system's I/O modules. A typical measurement signal may therefore follow the path:
Field instrument → field junction box → marshalling cabinet → I/O module → controller → control network → operator station
For an output signal, the flow is generally reversed:
Operator station or control algorithm → controller → I/O module → marshalling or termination assembly → field device
For example, a flow transmitter may measure the flow rate of a process stream and transmit the measurement as a 4–20 mA signal. The signal is routed through field wiring and termination equipment to an analog input module. The DCS controller then processes the measurement and compares it with the configured setpoint. A control algorithm, such as a PID controller, calculates the required output and sends a signal through an analog output module to a control-valve positioner. The positioner adjusts the valve to regulate the process flow.
Termination and marshalling equipment provides the physical interface between field wiring and the DCS I/O system. It may include terminal blocks, signal-conditioning devices, fuses, isolators, surge-protection devices, and other interface components. In conventional installations, each field signal is individually wired to a termination point and then connected to the appropriate I/O channel. Modern systems may use remote I/O, electronic marshalling, or digital communication networks to reduce conventional point-to-point wiring and allow I/O channels to be assigned more flexibly.
DCS installations commonly separate field wiring, termination equipment, I/O modules, controllers, and operator networks into different functional layers. The exact arrangement varies between systems and manufacturers. Redundant architectures may provide separate power supplies, communication paths, controllers, or I/O components to maintain operation following the failure of a system component.
Typical applications Distributed control systems (DCSs) are used primarily in large-scale industrial processes that are continuous, batch-oriented, or involve multiple interconnected process operations.
Processes and industries in which DCSs may be used include:
Chemical plants Petrochemical plants, oil refineries, Oil platforms, FPSO vessels, and LNG plants Pulp and paper mills, including associated quality control systems Power plants, including boiler, turbine, and balance-of-plant control systems Nuclear power plants Hydroelectric, thermal, and combined-cycle power plants Water treatment and water supply systems Sewage treatment plants Environmental control systems Food processing and beverage manufacturing Agrochemical and fertiliser production Pharmaceutical manufacturing Sugar refining and other food-processing industries Mining and mineral-processing operations Metallurgical and steel mill process plants Cement manufacturing and cement kilns Glass manufacturing and other process industries Automobile manufacturing and other large-scale manufacturing processes Agriculture and greenhouse automation District heating and other large-scale utility systems Desalination plants Oil and gas gathering, processing, and transportation facilities Renewable energy facilities and associated energy-storage systems
History
Evolution of process control operations Process control of large industrial plants has evolved through many stages. Initially, control would be from panels local to the process plant. However this required a large amount of human oversight to attend to these dispersed panels, and there was no overall view of the process. The next logical development was the transmission of all plant measurements to a permanently-staffed central control room. Effectively this was the centralisation of all the localised panels, with the advantages of lower manning levels and easier overview of the process. Often the controllers were behind the control room panels, and all automatic and manual control outputs were transmitted back to plant. However, whilst providing a central control focus, this arrangement was inflexible as each control loop had its own controller hardware, and continual operator movement within the control room was required to view different parts of the process.
With the coming of electronic processors and graphic displays it became possible to replace these discrete controllers with computer-based algorithms, hosted on a network of input/output racks with their own control processors. These could be distributed around plant, and communicate with the graphic display in the control room or rooms. The distributed control system was born.
The introduction of DCSs allowed easy interconnection and re-configuration of plant controls such as cascaded loops and interlocks, and easy interfacing with other production computer systems. It enabled sophisticated alarm handling, introduced automatic event logging, removed the need for physical records such as chart recorders, allowed the control racks to be networked and thereby located locally to plant to reduce cabling runs, and provided high level overviews of plant status and production levels.
Origins Early minicomputers were used in the control of industrial processes since the beginning of the 1960s. The IBM 1800, for example, was an early computer that had input/output hardware to gather process signals in a plant for conversion from field contact levels (for digital points) and analog signals to the digital domain.
The first industrial control computer system was built 1959 at the Texaco Port Arthur, Texas, refinery with an RW-300 of the Ramo-Wooldridge Company.