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Control Loop Foundation         Batch and Continuous Processes Terry Blevins   Principal Technologist
Presenters ,[object Object]
Mark Nixon, Manager, Future Architecture,[object Object]
Control Loop Foundation Short Course Short Course will provide a summary of key points and examples from Control Loop Foundation All  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 requirements The 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.
Introduction Control 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
Wiring Practices
Plant Organization Common terms used to describe plant organization are introduced. Plant Area – classification by name and area number Units within a process Area
Lab, Control Room, Lab  and Rack Room
Existing System – Electronic  and Pneumatic
Impact of DCS Systems
Integration of External System/Interface
Modern DCS Controller
Impact of Digital Communications  Ethernet Fieldbus – Foundation Fieldbus, Profibus Wireless  - WirelessHART
Wireless Impact ,[object Object]
Relatively simple - Obeys Network Manager
Gateway and Access Points
Allows control system access to WirelessHART Network Gateways
Manages communication bandwidth and routing,[object Object]
Measurement Introduction to devices used for basic measurement Magnetic flow meter Vortex flow meter Differential pressure for flow measurement Corilois flow meter Absolute and gauge pressure Temperature – RTD, thermocouple Level based on pressure/differential pressure Level - Radar
Device Calibration Concept of devices calibration and configuration is introduce. Role of hand held devices and EDDL is addressed
Analyzers Difference between sampling and situ analyzers is addressed Impact of sampling system on maintenance and measurement delay is highlighted
Analyzer Example A couple of common situ analyzers are addressed to show features and options Flue Gas O2  pH/ORP Calibration of analyzer and role of sample/hold when used in control is addressed.
Final Control Element Basic final control elements are addressed: Sliding stem valve Rotarty valve Damper drive Variable speed drive Block valve Advantages and limitations are discussed
Final Control Element Terminology Common terms associated with final control elements are defined Positioner Actuator Valve Body
Installed Characteristics Types of valve characteristics and their impact on installed characteristics is addressed
Field Wiring and Communications Installation of 2-wire vs 4-wire devices is addressed Common problems are address e.g. need for electric isolation when utilizing a 4-wire device
Fieldbus Installation Special requirements for a fieldbus installation are addressed Common terminology is defined: Multi-drop Power conditioner Terminator
Control System Documentation Documentation 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
Tag Convention – ISA S5.1
Representation of Signals and Instruments
Symbols for Field devices and Elements
Process Symbols
Symbol Example – P&ID Drawing
Symbol Example(Cont.)
Symbol Example(Cont.)
Symbol Example(Cont.)
Display Observing Color Usage Operator Graphics and Metrics An 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 Tools Basic tools for construction a display are discussed Dynamos, dynamic elements, faceplates, links for creating a display hierarchy
Performance Metrics  Example used to illustrate how operation metrics may be added to an operator display Benefits of integrating this type of information into the operator interface
[object Object]
A good understanding of these processes is required to design a control system for the plant.Process Characterization
Process Definition Process – Specific equipment configuration (in a manufacturing plant)  which acts upon inputs to produce outputs.
Process Terminology Controlled 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
Impact of Disturbance Input
Example – Lime Mud Filter Process
Example – Lime Mud Filter ( Cont.)
Pure Gain Process When 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 Process An 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 Process When 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 Process Example 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 Process ,[object Object]
The dynamic response is fully captured by identifying the process gain and the process time constant. ,[object Object]
First Order Plus Deadtime Process Most 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 Heater ,[object Object]
The process lag is caused by the heating process
The process deadtime is caused by transport delay,[object Object]
The net process response of these higher order systems can be approximated as first order plus deadtime.,[object Object]
Integrating Process ,[object Object]
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. ,[object Object]
Inverse Response Process ,[object Object]
Processes exhibiting this characteristic are said to have an inverse response.,[object Object]
The size or direction of the change in heat input may determine if an inverse response is obtained.  ,[object Object]
Example – Non-linear Process ,[object Object]
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.,[object Object]
Workshop - Process Characterization Three example processes are include in workshop First order plus deadtime Integrating Inverse response Web site is accessed to perform step test.  Only a web browser is needed – no software to install.
Control Objective For 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 Limit For 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 Variability Production improvement is obtained by operating closer to product specification or operating limit.
Example - Ammonia Plant
Example - Ammonia Plant (Cont.)
Example - Ammonia Plant (Cont.)
Other Control Objectives
Balancing Control Complexity and Benefits Various techniques may be used to improve the control of a process As the complexity of the control system increases, so does cost for operator training and maintenance The complexity (cost) of the control system should be balanced with the benefits provided The benefits of control improvement may be influenced by market conditions i.e. value of product, cost of feedstock, energy cost
Single Loop Control In some cases manual control may be appropriate Manual Loader Block may be used to implement manual control
Manual Control Implementation
Processing of Analog Input Signal
Impact of Aliasing
Setup of Anti-aliasing Filter
Processing by Analog Input Block
Filtering Provided by Analog Input Block
Manual Loader Block
Analog Output Block
Analog Output Block - Rate Limiting
Analog Output Block – Increase to Close Option
Feedback Control
Proportional Only Control
Proportional Plus Integral (PI) Control
Proportional, Integral, Derivative (PID) Control
PID Structure Selection
PID Direct/Reverse Selection
PID Function Block
PID Form – Standard and Series
Setting PID Form and Structure
Block Mode – Selection of Source of SP and OUT
Target Modes of Block
Other Actual Modes of Block
Duty Cycle Control
Duty Cycle Control (Cont.)
Increase-Decrease Control – Motor Driven Actuator
Workshop – Feedback Control
Tuning and Loop Performance – Default Setting
Manual Tuning Technique
Tools to Automate Tuning Example base on DeltaV Insight On-demand Tuning
Impact of Sticky Valve
Use of Signal Characterizer to Compensate for Non-linearity
Characterizer Setup
Multi-loop Control - Feedforward Control
Feedforward Control Implementation
Commissioning Dynamic Compensation
Workshop – Feedforward Control
Cascade Control
Example – Boiler Steam Temperature
Cascade Control Implementation Selecting 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.
Workshop – Cascade Control
Override Control
Example – Override Control
Override Control Implementation
Workshop – Override Control
Control Using Two Manipulated Parameters Three methods Addressed:  Split Range Control  Valve Position Control Ratio Control
Split Range Control Implementation
Split Range Setup
B A Example – Split Range Control
Workshop – Split Range Control
Valve Position Control
Valve Position Control Implementation
Example – Valve Position Control
Workshop – Valve Position Control
Ratio Control
Ratio Control Implementation
Example – Ratio Control In this example the ratio setpoint is adjusted using feedback control based on a downstream analysis of the blended material
Workshop – Ratio Control
Process Simulation for Ratio Workshop
Model Predictive Control (MPC) Operating Within Process Constraint
MPC May be Layered on Existing Control
Workshop – Model Predict Control
Process Modeling
Simulation Diagram
Simulation Module
Example – Process Simulation Composite
Workshop – Process Modeling
Application – Boiler Drum Level
Batch Reactor
Batch Reactor- Processing
Batch Reactor - Control
Continuous Reactor
Continuous Reactor - Control
Single Fuel Power Boiler
Power Boiler Combustion Control
Distillation Column
Distillation Column Control
Ammonia Plant H/N Ratio Control
Ammonia Plant H/N Ratio Control (Cont.)
Control Loop Foundation Web Site

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