1 A Introduction to Process Control

  Department of Engineering Physics ITB

Practical Industrial Process Control:

  

Practical Industrial Process Control:

Understanding, Tuning & Autotuning Control Loops

  

Understanding, Tuning & Autotuning Control Loops

  Edi Leksono

  Department of Engineering Physics Institut Teknologi Bandung June 2003

Training Objectives Training Objectives

  Design of P, PI, PD and PID for specific process objectives or product specifications

  Practical Troubleshooting ^GOALS

  

  Tuning & Autotuning

  

  Design of feedback, feedforward, cascade, feedforward/ feedback, feedforward/feedback + cascade controls

  

  

  Introduction to process control

  Analysis of dynamic systems

  

  Dynamic modelling

  

  Elements of process control loop

  

  

Road Map of the Training Road Map of the Training

   First, we will visit all the block elements of the control system,especially the controller

• Controller Actuator Process

  Controller Actuator Process Sensor +

  Sensor + Transmitter

  Transmitter 

  Then, analyze the whole system all together 

  Then, consider the variations of the elements

Time Table Time Table

   _Time Day _{Opening, Day 1 Day 2 Day 3 Day 4 Day 5 08.00-09.30 PID Control I of PID Controller Cascade Control I Feedforward Industrial Process Introduction to Control} Tuning Methods Feedback/ _{+ Lab. III Control + Lab 10.00-11.30 Actuators PID Control II Methods of PID Controller + Lab. Autotuning Cascade Control Feedforward + II + Lab. Cascade Control} Feedback/ _{+ Lab 12.30-14.00 Sensor/Transmitter, Practical Feedforward Filtering Troubleshooting I Control I of PID Controller} Tuning Methods _{+ Lab. I Demo 14.30-16.00 Process Dynamic Modelling of PID Controller} Tuning Methods _{+ Lab. II Troubleshooting II Control II + Lab. Practical Feedforward Final Test, Closing}

  Department of Engineering Physics ITB

Introduction to

  

Introduction to

Process Control

  Process Control

  Edi Leksono

  Department of Engineering Physics Institut Teknologi Bandung June 2003

Session Outlines & Objectives Session Outlines & Objectives Outlines

  

  The importance of process control

  

  Basic concepts of process control

Objectives

  

  Understand what process control is

  

  Know the terms of process control system

  

  Identify the elements of process control system

  

  Understand the importance of process control

  

  Know the type of process control strategies

Definition (1) Definition (1)

   Process

• A series of interrelated actions which transform material It covers all resources that are involved in the process and talks about process “inputs” (e.g. resources, raw material) and “outputs” (e.g. finished product)

  Energies Out Raw Materials Products

  Process Energies Out

   Control

• To maintain desired conditions in a physical system by adjusting selected variables in the system

Definition (2) Definition (2)

   Process Control

• To maintain desired conditions in a physical system by adjusting selected variables in the system in spite of disturbances affecting the system and observation noise

  Corrective Action Process Data Knowledge Information

Daylife Example: Driving a Car Daylife Example: Driving a Car

   Control Objective (Setpoint):

• Maintain car in proper lane

   Controlled variable:

  Brain: Control calculation Eyes:

  Sensor Steering wheel: Actuator

• Location on the road

   Manipulated variable:

• Orientation of the front wheels

   Actuator:

• Steering wheel

   Sensor:

• Driver’s eyes

   Controller:

• Driver

   Disturbance:

• Curve in road

   Noise:

• Rain, fog

• Maintain temperature
• Outlet temperature of product stream
• Steam flow
• Control valve on steam line
• Thermocouple on product stream
• Temperature controller

  Feed Condensate Product Stream Steam

   Control Objective (Setpoint):

   Controlled variable:

   Manipulated variable:

   Actuator:

TT TC Industrial Example #1: Heat Exchanger Industrial Example #1: Heat Exchanger

   Sensor:

   Controller:

   Disturbance:

• Changes in the inlet feed temperature

   Noise:

• Measurement noise

  

Industrial Example #2: Liquid Level Control

Industrial Example #2: Liquid Level Control

   Control Objective (Setpoint):

• Maintain level
• Fluid level in the tank
• Fluid flow
• Control valve on fluid line
• Level transmitter on the tank
• Level controller
• Changes in the inlet feed flow
• Measurement noise

Sensor

   Controlled variable:

   Manipulated variable:

   Actuator:

   Sensor:

   Controller:

   Disturbance:

   Noise:

  Fluid

  

• Measure process variable

  

  Transmitter

• Convert the measured process variable into standard signal

  

  Controller

• Drive actuator by giving an appropriate controller output signal

  

  Actuator

• Adjust manipulated variable based on the value of the controller output signal

  

  Process

  Elements of Process Control Loop Elements of Process Control Loop

• Physical system to be controlled

The Terms I The Terms I

   Control Objective (Setpoint, SP)

   Controlled Variable (CV) or Process Variable (PV)

   Measured Process Variable (PV _m )

   Controller Output (CO)

   Manipulated Variable (MV)

   Final Control Element (Actuator)

   Sensor/Transmitter

   Controller

   Disturbance Variable (DV)

   Measurement Noise

Goal of Process Operation Goal of Process Operation

  24 hours process operation? _{Hmm… I think, to achieve those, we need to continuously monitor & control the process} 24 hours a day, _{7 days a week!!!}

  

  Safety & Reliability

  

  Product Specification

  

  Environmental Regulation

  

  Operating Constraint

  

  Efficiency

  

  Maximum profit

Safety and Reliability Safety and Reliability

  

  The control system must provide safe operation

• Alarms, safety constraint control, start-up and

  shutdown

  

  A control system must be able to “absorb” a variety of disturbances and keep the process in a good operating region

• Feed composition upsets, temporary loss of utilities (e.g., steam supply), day to night variation in the process
• Products with reduced variability

  Time Im pu ri ty

  C on ce nt ra tio n

  Limit Time

  Im pu ri ty

  C on ce nt ra tio n

  Limit Old Controller New Controller

  

  Quality

   For many cases, reduced variability products are in high demand and have high value added (e.g. feedstocks for polymers)

 Product certification procedures (e.g., ISO 9000) are used

  to guarantee product quality and place a large emphasis on process control

  Product Specification Product Specification

Environmental Regulation Environmental Regulation

   Various government laws may specify that the temperatures, concentrations of chemicals, and flow

rates of the effluents from a process be within certain

limit Examples:

  Regulations on the amounts of SO • ₂ that a process can eject to the atmosphere, and on the quality of water returned to a river or a lake

Operational Constraint Operational Constraint

   All real process have constrained inherent to their operation which should be satisfied throughout the operation Examples:

• Tank should not overflow or go dry
• Distillation column should not be flooded
• Catalytic reactor temperature should not exceed an upper limit since the catalyst will be destroyed

Efficiency Efficiency

   The operation of a process should be as economical as possible in utilization of raw material, energy and capital

Maximizing the Profit of a Plant (1) Maximizing the Profit of a Plant (1)

  

  The operation of a process may many times involves controlling against constraints

  

  The closer that you are able to operate to these constraints, the more profit you can make

  Example:

• Maximizing the product production rate usually involving controlling the process against one or more process constraints

  Time

  Im pu ri ty

  C on ce nt ra tio n

  Limit

  Time

  Im pu ri ty

  C on ce nt ra tio n

  Limit

  New Controller Improved Performance

  Constraint control example: A reactor temperature control  At excessively high temperatures the reactor will experience a temperature runaway and explode  But the higher the temperature the greater the product yield  Therefore, better reactor temperature control allows safe operation at a higher reactor temperature and thus more profit

  Maximizing the Profit of a Plant (2) Maximizing the Profit of a Plant (2)

   1960s Pneumatic analog instrumentation, controllers, and computing modules  1970s Electronic analog instrumentation, controllers, and computing modules _{• Direct digital control with special algorithms programmed in main frame computer}

   1980s Electronic analog instrumentation and digital distributed control systems (DCS) _{• Supervisory and model predictive control configured in special purpose computers}

   1990s Smart analog instrumentation, valves, and digital distributed control systems _{• Supervisory and model predictive control configured in special purpose computers • Neural networks, online diagnostics, and expert systems in special purpose computers}

  The History of Process Control The History of Process Control

• _{Real time optimization using model libraries in special purpose computers}

  

2000s Field bus based digital smart instrumentation, valves, and control systems

_{• Digital bus takes full advantage of smartness and accuracy of instrumentation and valves • Some fast PID controllers such as flow and pressure go to the field transmitter or valve}

• _{Model predictive control, neural networks, online diagnostics, and expert systems are integrated into the graphically configurable field bus based control systems and move to PCs • APC Infrastructure, interface, and engineering costs decrease by an order of magnitude}
• _{APC projects use consultants more for front end and commissioning than for whole job • APC software tools are easy enough for the average process and control engineer to use}

Common Types of Control Strategy Common Types of Control Strategy

  

  Manual vs. Automatic

  

  Servo vs. Regulator

  

  Open-loop vs. Closed-loop

  

  Control strategies

• Feedback Control
• Feedforward Control
• Cascade Control

  

  Single-Input Single-Output (SISO) vs. Multi-Input Multi- Output (MIMO, also known as multivariable)

Manual vs. Automatic Manual vs. Automatic

  

  Manual _{Temperature indicator} ^{Should I adjust}

• Human has to adjust the MV to
_{the valve or} obtain the desired value of the PV _{should I run?} based on observation and prior experiences Emergency _cooling

  

  Automatic

• The computer (or other device) autonomously controls the process and may report status back to a operator

  Question: Why manual override has to be included in every automatic control systems?

Regulator vs. Servo Regulator vs. Servo

• Follow constant setpoint, overcoming the disturbance
• Follow the changing setpoint

  75.5 C… _{75.3 C… 75.4 C…} ^o _{o o} ^{7.00 AM: 80 C…} _{8.00 AM: 70 C… 9.00 AM: 60 C…} ^o _{o o} Question: How to achieve both objectives simultaneously?

  

  Regulatory control

   Servo control

Open-loop vs. Closed-loop Open-loop vs. Closed-loop

  DV 

  Open-loop

• Process is controlled based on

  predetermined scenario

  Process Process

  Ex.: When food is done in an oven, _Decisions timers on outdoor lights Controller

  Controller SP DV

  

  Closed-loop

• The information from sensor is

  used to adjust the MV to obtain

  Process Process

  the desired value of the PV _Decisions

  Controller Controller

  SP

  

  Feedback Control

• Corrective action based on process variable (PV)

  Advantage Requires no knowledge of the source or nature of disturbances, and minimal detailed information about how the process itself works

  Disadvantage Controller takes some corrective actions after some changes occurs in process variable PV

  DV SP PV

  Feedback Controller Feedback Controller

  CO Process

  Process Control Strategies (1) Control Strategies (1)

Control Strategies (2) Control Strategies (2)

   Feedforward Control

• Based on the measurement of disturbance (DV)  feedforward controller can respond even before any changes occurs in PV

  DV CO PV Feedforward

  SP Feedforward Process

  Process Controller

  Controller Advantage

  Controller takes some corrective actions before the process output is different

from the setpoint  theoretically, perfect disturbance rejection is possible!

Disadvantage

   Requires process model which can predict the effect of disturbance on PV  If there are some modeling error, feedforward control action will be erroneous (no corrective action)  Feedforward controller can be quite complex

Control Strategies (3) Control Strategies (3)

• Feedforward controller will adjust CO as soon as the DV is detected
• If the feedforward action is not enough due to model error, measurement error and etc., feedback controller will compensate the difference

  DV SP

  Feedforward/ Feedback Controller

  Feedforward/ Feedback Controller

  Process Process

  

  Feedback/Feedforward Control

Control Strategies (4) Control Strategies (4)

• The disturbance DV

  DV SP

  Outer Feedback Controller

  Outer Feedback Controller

  Inner Feedback Controller

  Inner Feedback Controller

  Inner Process

  Inner Process

  Outer Process

  Outer Process

  DV

₁

CO Inner loop Outer loop

  

  Cascade Control

  1

  arising within the inner loop are corrected by the inner controller before it can affects the PV of the outer one Example: Control valve + positioner

Control Strategies (5) Control Strategies (5)

  DV SP

  Outer Feedback Controller

  Outer Feedback Controller

  Inner Feedback Controller

  Inner Feedback Controller

  Inner Process

  Inner Process

  Outer Process

  Outer Process

  

DV

₁ CO Inner loop Outer loop

  

  Feedback/Feedforward + Cascade Control

SISO vs. MIMO SISO vs. MIMO

  

  Based on how many PV and MV we have in a process

  SISO

MIMO

  DVs

  DV … …

   … … Process

  Process COs PVs _Decisions Process _Decisions Process

  … … … … Controller

  … … Controller

  Controller Controller

  

  Closeness to setpoint

  

  Short transient to one setpoint to other setpoint

  

  Smaller overshoot and less oscillation

  

  Smooth and minimum changes of variable manipulation

  

  Minimum usage of raw materials and energy

  1

  2

  2 1, 2 1, 2

  1

  2 Regulator Servo

Performances of Process Control System

  

Performances of Process Control System

  

  Servo control

  Oscillation

  

  Overshoot

  

  Transient response

  

  MIMO control

  

  SISO control

  

  Regulatory control

  

  

  Manual control

  Cascade control

  

  Feedforward control

  

  Feedback control

  

  Closed-loop control

  

  Open-loop control

  

  Automatic control

  

  The Terms II The Terms II

Development of a Control System (1) Development of a Control System (1)

  1. Open Loop Analysis

• What kind of system is considered?

  2. Performance Specifications

• How is the system required to behave?

  

 The desired performance must be expressed in terms of the different

performance measures that are chosen  Often, depends on the type of control problem to solve

  3. Control Configuration

• Which signals are used to calculate the control signal?

   Depending on the plant the desired performance specifications and the allowed complexity of the control system  Depending on the type and the number of input signals to the controller different configurations are recognized

Development of a Control System (2) Development of a Control System (2)

  4. Control Law

• Which algorithm is used to calculate the control signal?

  5. Parameter Design (Tuning)

• Which are the parameters of the algorithm to calculate the control signal?

  6. Evaluation

• How will the controlled system behave in theory?  simulation!

  7. Implementation and Verification

• How will the control system be realized?
• How does the controlled system behave in practice?
• The controller will be implemented and one will verify whether the system is controlled as expected

The Terms III The Terms III

  

  Control law (algorithm)

  

  Parameter design (tuning)

  

  Computer simulation

Session Summary Session Summary

  

  Control has to do with adjusting manipulated variables of the process to maintain controlled variables at desired values

  

  All control loops have a controller, an actuator, a process, and a sensor/transmitter

  

  Various controller strategies can be realized to achieve desired process objectives & product specifications