Temperature Control
Introduction
Temperature, pressure, flow, and level are the four
most common process variables. Temperature is the most
important one because it provides a critical condition
for combustion, chemical reaction, fermentation, drying,
calcination, distillation, concentration, extrusion,
crystallization, and air conditioning. Poor temperature
control can cause major safety, quality, and productivity
problems. Although highly desirable, it is often difficult
to control the temperature.
Why Temperature Control Can Be Difficult
The many reasons why a temperature loop is difficult
to control are listed and described in the following
table:
| Reason |
Example |
Control
Headache |
| The slowness of the temperature loop |
Furnaces, kilns, buildings, and operating units
with large heat capacity all have slow temperature
loops. |
Manual tuning of a slow temperature loop requires
persistence and patience. |
| Time-varying |
It is often much faster to add heat to an operating
unit than to take the heat away, if cooling is not
available. Thus, the time constant can vary dramatically
depending on if the temperature is going up or down.
|
Varying time delays and time constants can easily
cause a PID to oscillate or become sluggish. PID
can be tuned for certain operating conditions but
may fail when the process dynamics change. |
| Nonlinear |
Control valves: the dead band and slip-stick action
make the temperature loop nonlinear. |
A PID or model-based controller may work well
in its linear range and fail in its nonlinear range. |
| Multi-zone temperature control |
Glass forehearth furnaces, plastic extruders,
and rapid thermal processing units require control
of temperature zones. |
This MIMO (multi-input-multi-output) process cannot
be effectively controlled by using SISO controllers
due to interactions between zones. |
| Large load changes |
Steam generators in co-generation plants have
to deal with large steam load changes due to variations
in steam users’ operating conditions. |
If the load doubles, it requires twice the amount
of heat to maintain the temperature. Feedforward
control is often required. |
| Large inflow changes |
Tomato hotbreaks for tomato paste production:
Tomatoes are dumped in by truck loads causing significant
inflow variations. |
If the inflow is solid, it is difficult to measure
the flow rate; so feedforward control is not a viable
solution. |
| Fuel changes |
Steam generators used in forest product industries
where wood chips are used as a supplement fuel.
Fluidized-bed boilers that burn low grade fuel.
|
The change in heating value due to a changing
fuels can cause major disturbances to the temperature
control loop. |
| Nonlinear and high-speed |
Rapid thermal processing (RTP) unit for wafer
treatment or for thermal testing of materials. |
Ramping temperature up and down across a wide
range at high speed. |
| A multi-input-single-output (MISO) process |
An air-handling unit (AHU) of a building control
system manipulates heating valve, cooling valve,
and damper based on split-range control. |
One controller has to deal with multiple processes
such as heating and cooling. A fixed controller
like PID needs to be re-tuned when the control mode
changes. |
| A single-input-multi-output (SIMO) process |
Distillation columns: both the bottom temperature
and tray temperature need to be controlled. But
the reboiler steam flow is the only manipulated
variable. |
The controller has only one variable to manipulate
but needs to control or maintain 2 or more process
variables. Single-loop controllers like PID aren’t
sufficient. |
MFA Control Solutions
Since temperature control problems can vary so much,
the following table provides a roadmap to allow you
select the appropriate MFA controller to solve a specific
temperature control problem.
| Reason |
Selected
MFA Controller |
What
Can This MFA Do? |
| The slowness of the temperature loop |
SISO MFA controller |
MFA adapts. No manual tuning is required. |
| Time-varying |
SISO MFA controller, or
Time-varying MFA controller
|
MFA adapts to deal with process time constant
and delay time changes.
Time-varying MFA can control processes with very
large time constant and delay time changes. Configuration
is very simple. |
| Nonlinear |
Nonlinear MFA controller |
Nonlinear MFA controls extremely nonlinear processes
with no nonlinear characterization required. |
| Multi-zone temperature control |
MIMO MFA controller or
Feedback/Feedforward MFA controller |
MIMO MFA controls multivariable processes. Interactions
among temperature zones can be decoupled. |
| Large load changes |
Feedback/Feedforward MFA controller |
Feedforward MFA controller can be easily configured
to force the controller to make quick adjustments
to compensate for the load changes. |
| Large inflow changes |
SISO MFA controller |
MFA provides quick control response to compensate
for large inflow changes. |
| Fuel changes |
SISO MFA controller |
MFA adapts to the new operating point to compensate
for the fuel change. |
| Nonlinear and high-speed |
High-speed Nonlinear MFA controller |
After choosing a Nonlinearity factor during configuration,
the Nonlinear MFA can effectively control this process
with changing nonlinear characteristics. |
| A multi-input-single-output (MISO) process |
SISO MFA with split-range design or
SIMO MFA controller
|
MFA adapts to new operating conditions with no
manual tuning required. |
| A single-input-multi-output (SIMO) process |
MISO MFA controller |
This special MFA controller manipulates only one
variable to control or maintain multiple process
variables inside their specification ranges. |
Summary
Based on the core MFA control method, various MFA controllers
have been developed to solve specific control problems.
Without having to build on-line or off-line process
models, an appropriate MFA controller can be selected
and configured to control a complex temperature loop.
MFA provides easy and effective solutions to temperature
control problems that were previously unsolved.
Case Studies
To read more about implementations of CyboSoft’s
MFA temperature control solutions, click on the following
case studies:
Model-Free
Adaptive Control of Tomato Hot Breaks
Model-Free
Adaptive Control of Multi-Zone Temp Loops
Model-Free
Adaptive Control of Rotary Kilns
Model-Free
Adaptive Control of Fluidized-Bed Boilers
Model-Free
Adaptive Control of Steam Injection Systems
MFA
Control and Optimization of Distillation Columns
Model-Free
Adaptive Control of Oil Refinery Furnaces
Model-Free
Adaptive Control of Batch Reactors
|
