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Temperature Control


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.


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


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