Control Loop Foundation - Batch And Continous Processes

Control Loop Foundation Batch and Continuous ProcessesTerry Blevins Principal Technologist

PresentersTerry Blevins, Principal Technologist

Mark Nixon, Manager, Future ArchitectureControl Loop Foundation Short Course Introduction Background – Historic Perspective Measurement – Basic Transmitter Types, Limitations Analyzers – Examples of On-line Analyzers Final Elements – Valves and Variable Speed DrivesField Wiring and Communications – Traditional, HART, FF , WirelessHART Control Strategy Documentation – Plot Plan, Flow Sheet, P&ID, Loop Diagram Operator Graphics and Metrics – Considerations in Display Design Process Characterization – Identifying process dynamics and gain Control Objectives Single Loop Control – PID basics, selecting PID structure, action Tuning and Loop Performance – Manual and automated tuning techniques Multi-loop Control – Feedforward, Cascade, Override, Split-range Model Predictive Control – Addressing Difficult Dynamics, Interactions Process Modeling – Process simulation for Checkout/Training Applications – Continuous, Batch, Combustion, Distillation Accessing the book web Site Open Discussions book drawing & Wrap-up

Control Loop Foundation Short CourseShort Course will provide a summary of key points and examples from Control Loop FoundationAll workshops and application examples in the book are based on DeltaV control capability. This book is available at www.isa.org and this week at the ISA booth.The application section is designed to show how control techniques may be combined to address more complex process requirementsThe book web site may be accessed to perform the workshops and to obtain hands-on experience using application example. Copies of the modules and trends may be downloaded from the web site and imported into a DeltaV system. A new class, Control Loop Foundation - Course 9025, Is available through the education department.

IntroductionControl Loop Foundation address the concepts and terminology that are needed to work in the field of process control. The material is presented in a manner that is independent of the control system manufacturer. Much of the material on the practical aspects of control design and process applications is typically not included in process control classes taught at the university level. The book is written to act as a guide for engineers who are just starting to work in this field. Experienced control engineers will benefit from the application examples on process control design and implementation of multi-loop control strategies.

Background - Different Construction Techniques

Plant OrganizationCommon terms used to describe plant organization are introduced.Plant Area – classification by name and area numberUnits within a process Area

Lab, Control Room, Lab and Rack Room

Existing System – Electronic and Pneumatic

Integration of External System/Interface

Impact of Digital Communications EthernetFieldbus – Foundation Fieldbus, ProfibusWireless - WirelessHART

Wireless ImpactWireless Field Devices

Relatively simple - Obeys Network Manager

Allows control system access to WirelessHART Network Gateways

Manages communication bandwidth and routingImpact of Standard on ControlISA88 – Batch terminologyIEC 61131 – Function blocks, Ladder Logic, Structured Text, Sequential Function Charts.IEC 61804 – Function blocks for the process industry,

MeasurementIntroduction to devices used for basic measurementMagnetic flow meterVortex flow meterDifferential pressure for flow measurementCorilois flow meterAbsolute and gauge pressureTemperature – RTD, thermocoupleLevel based on pressure/differential pressureLevel - Radar

Device CalibrationConcept of devices calibration and configuration is introduce.Role of hand held devices and EDDL is addressed

AnalyzersDifference between sampling and situ analyzers is addressedImpact of sampling system on maintenance and measurement delay is highlighted

Analyzer ExampleA couple of common situ analyzers are addressed to show features and optionsFlue Gas O2 pH/ORPCalibration of analyzer and role of sample/hold when used in control is addressed.

Final Control ElementBasic final control elements are addressed:Sliding stem valveRotarty valveDamper driveVariable speed driveBlock valveAdvantages and limitations are discussed

Final Control Element TerminologyCommon terms associated with final control elements are definedPositionerActuatorValve Body

Installed CharacteristicsTypes of valve characteristics and their impact on installed characteristics is addressed

Field Wiring and CommunicationsInstallation of 2-wire vs 4-wire devices is addressedCommon problems are address e.g. need for electric isolation when utilizing a 4-wire device

Fieldbus InstallationSpecial requirements for a fieldbus installation are addressedCommon terminology is defined:Multi-dropPower conditionerTerminator

Control System DocumentationDocumentation that is typically generated for a control system installation are addressed.The purpose of each document is explained.Reference provided to ISA-5.4 standard for Instrument Loop Diagrams

Representation of Signals and Instruments

Symbols for Field devices and Elements

Symbol Example – P&ID Drawing

Display Observing Color UsageOperator Graphics and MetricsAn operator interface design is addressed by Alarm Standard EEMUA 191 Advocates that alarms should be in alarm color. Pipes, pumps, valves, etc. should not be in alarm colors, or any other bright color.

Display ToolsBasic tools for construction a display are discussedDynamos, dynamic elements, faceplates, links for creating a display hierarchy

Performance Metrics Example used to illustrate how operation metrics may be added to an operator displayBenefits of integrating this type of information into the operator interface

A plant may be thought of as being made up of a series of processes.

A good understanding of these processes is required to design a control system for the plant.Process Characterization

Process DefinitionProcess – Specific equipment configuration (in a manufacturing plant) which acts upon inputs to produce outputs.

Process TerminologyControlled output (controlled parameter) – Process output that is to be maintained at a desired value by adjustment of process input(s). Setpoint – Value at which the controlled parameter is to be maintained by the control system. Manipulated input (manipulated parameter) – Process input that is adjusted to maintain the controlled parameter at the setpoint. Disturbance input – Process input, other than the manipulated input, which affects the controlled parameter. Constraint output (constraint parameter) – Process output that must be maintained within an operating range. Constraint limit – Value that a constraint parameter must not exceed for proper operation of the process.Other input – Process input that has no impact on controlled or constraint outputs.Other output – Process output other than controlled or constraint outputs.

Example – Application of Terminology

Example – Lime Mud Filter Process

Example – Lime Mud Filter ( Cont.)

Pure Gain ProcessWhen the process output tracks the process input except for a change in signal amplitude, the process is known as a pure gain. The change in signal amplitude is determined by the process gain. For a step change in process input, the process gain is defined as the change in the process output divided by the change in process input

Example – Pure Gain ProcessAn example of a pure gain process is the jack shaft used in some boiler combustion control systems.Gain is determine by the length of the lever arms attached to the jack shaft.

Pure Delay ProcessWhen the process output tracks the process input except for a delay in the output signal, the process is know as a pure delay process. For a step change in the process input, process deadtime is defined as the time from the input changing until the first affect of the change is seen in the process output.

Examples – Pure Delay ProcessExample of pure delay processes are a conveyor belt and a pipeline.Delay is the result of transport time and will vary with the speed of the belt or the flow rate through the pipe.

First Order ProcessWhen process output immediately begin to respond to a step change in a process input and the rate of change is proportional to its current value and the final value the output will achieve, the process is know as a first order process.

The dynamic response is fully captured by identifying the process gain and the process time constant. Example – First Order ProcessAn example of a pure lag process is a tank with outlet flow determined by tank level and the outlet flow restriction caused by the orifice.The level will settle at a value which results in an outlet flow that matches the inlet flow.

First Order Plus Deadtime ProcessMost process in industry may be approximated as first order plus deadtime processes. A first order plus deadtime process exhibits the combined characteristics of the lag and delay process.

Example – Steam HeaterAn example of a first order plus deadtime process is a steam heater.

The process lag is caused by the heating process

The process deadtime is caused by transport delayHigher Ordered SystemsThe dynamic response of a process is the results of many components working together e.g. I/P, Valve actuator, heat or fluid/gas transport, etc.

The net process response of these higher order systems can be approximated as first order plus deadtime.Combined Impact of Process Dynamics

Integrating ProcessWhen a process output changes without bound when the process input is changed by a step, the process is know as a non-self- regulating or integrating process.

The rate of change (slope) of the process output is proportional to the change in the process input and is known as the integrating gain. Example – Integrating ProcessAn example of a non-self-regulating process is tank level where outlet flow is established by a gear pump. If the inlet flow does not match the outlet flow, then level will continue to change until the tank overflows or runs dry.

Inverse Response ProcessFor a few processes, the initial change in the process output to a step change in a process input will be in the opposite direction of the final output change.

Processes exhibiting this characteristic are said to have an inverse response.Example – Inverse Response ProcessThe level of a vertical thermosiphonreboiler in a distillation column may exhibit an inverse response to a rapid increase in heat input.

The size or direction of the change in heat input may determine if an inverse response is obtained. Process Linearity

Example – Non-linear ProcessMost processes may be approximated as linear over a small operating range. However, over a wide range of operation, processes may exhibit some non-linearity.

A common cause of non-linearity is a change in process gain – reflecting the installed characteristics of the final control element i.e. valve acting with the other equipment making up the process, as illustrated in this example.Workshop – Use of Process Simulation

Workshop - Process CharacterizationThree example processes are include in workshopFirst order plus deadtimeIntegratingInverse responseWeb site is accessed to perform step test. Only a web browser is needed – no software to install.

Control ObjectiveFor the case, production is greatest when the band of variation is reduced to zero and the process parameter is maintained at the value corresponding to maximum production

Impact of Operating Target To benefit from improvement in control, the loop must operate at the target that provides maximum production.The plant design conditions may be used as a guide in establishing setpoints for best operation

Operating at a LimitFor this case, maximum production is obtained by maintaining the process parameter at a limit determined by some plant limitation. How close to the limit you can operate is determined by the quality of the control

Impact of Reduced VariabilityProduction improvement is obtained by operating closer to product specification or operating limit.

Example - Ammonia Plant (Cont.)

Balancing Control Complexity and BenefitsVarious techniques may be used to improve the control of a processAs the complexity of the control system increases, so does cost for operator training and maintenanceThe complexity (cost) of the control system should be balanced with the benefits providedThe benefits of control improvement may be influenced by market conditions i.e. value of product, cost of feedstock, energy cost

Single Loop ControlIn some cases manual control may be appropriateManual Loader Block may be used to implement manual control

Processing of Analog Input Signal

Processing by Analog Input Block

Filtering Provided by Analog Input Block

Analog Output Block - Rate Limiting

Analog Output Block – Increase to Close Option

Proportional Plus Integral (PI) Control

Proportional, Integral, Derivative (PID) Control

PID Form – Standard and Series

Setting PID Form and Structure

Block Mode – Selection of Source of SP and OUT

Increase-Decrease Control – Motor Driven Actuator

Tuning and Loop Performance – Default Setting

Tools to Automate TuningExample base on DeltaV Insight On-demand Tuning

Use of Signal Characterizer to Compensate for Non-linearity

Multi-loop Control - Feedforward Control

Feedforward Control Implementation

Commissioning Dynamic Compensation

Workshop – Feedforward Control

Example – Boiler Steam Temperature

Cascade Control ImplementationSelecting FRSI_OPT for dynamic reset in primary loop and CONTROL_OPTS for Use PV for BKCAL_OUT in secondary loop can often improve dynamic response.

Override Control Implementation

Control Using Two Manipulated ParametersThree methods Addressed: Split Range Control Valve Position ControlRatio Control

Split Range Control Implementation

BAExample – Split Range Control

Workshop – Split Range Control

Valve Position Control Implementation

Example – Valve Position Control

Workshop – Valve Position Control

Example – Ratio ControlIn this example the ratio setpoint is adjusted using feedback control based on a downstream analysis of the blended material

Process Simulation for Ratio Workshop

Model Predictive Control (MPC)Operating Within Process Constraint

MPC May be Layered on Existing Control

Workshop – Model Predict Control

Example – Process Simulation Composite

Application – Boiler Drum Level

Power Boiler Combustion Control

Ammonia Plant H/N Ratio Control

Ammonia Plant H/N Ratio Control (Cont.)

Control Loop Foundation Web Site

Control Loop Foundation - Batch And Continous Processes

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