Conventional controllers like PID and many
advanced control methods are useful to control linear
processes. In practice, most processes are nonlinear.
If a process is a just little nonlinear, it can be treated
as a linear process. If a process is severely nonlinear,
it can be extremely difficult to control.
CyboSoft offers an innovative Model-Free Adaptive (MFA)
control solution for controlling severely nonlinear
processes without having to build process models and
retune controller parameters. It also eliminates the
need of traditional nonlinear characterization allowing
the user to easily configure and launch Nonlinear MFA
Why is Nonlinear Control Difficult?
Nonlinear control is one of the biggest challenges
in modern control theory. While linear control system
theory has been well developed, it is the nonlinear
control problems that present the most headaches. Nonlinear
processes are difficult to control because there can
be so many variations of the nonlinear behavior.
Traditionally, a nonlinear process has to be linearized
first before an automatic controller can be effectively
applied. This is typically achieved by adding a reverse
nonlinear function to compensate for the nonlinear behavior
so the overall process input-output relationship becomes
somewhat linear. It is usually a tedious job to match
the nonlinear curve; and process uncertainties can easily
ruin the effort.
Nonlinear MFA vs. PID Controller
The following trends show the Nonlinear MFA
controller (top) is able to control a severely nonlinear
process throughout the entire operating range (linear
and nonlinear). PID works fine in the linear range but
fails to control in the nonlinear range.
A flow or pressure loop is a typical nonlinear process
that can cause the actuator to lose its authority in
different operating conditions. Inevitable wear and
tear on a valve can also make a linear valve nonlinear.
The variable frequency drive (VFD) has become a popular
flow regulator because it saves energy. However because
of its nonlinear nature, it adds a nonlinear component
to the process.
The dissolved oxygen used to cultivate cells in a bio-tech
micro reactor is another example of a nonlinear process.
As cells grow, they suddenly start to consume much more
oxygen. Since the number of bio-tech experiments is
huge and the types of cells to be grown can vary significantly,
it is difficult and costly to apply traditional nonlinear-characterization
in solving this nonlinear problem.
Nonlinear MFA can tightly control a nonlinear
process within its full control range, even when the
process gain changes hundreds of times. In a Nonlinear
MFA, there is no linearization calculation or process
model. The MFA controller gain is simply set at its
nominal point and not retuned.
This general-purpose, powerful solution can be easily
implemented. No special knowledge or experience with
advanced control, nonlinear characterization, or process
modeling is required. Tough nonlinear loops can be controlled
resulting in smoother operations, longer actuator life,
higher product quality and production efficiency, and
reduced waste in energy and material.
To read more about implementations of CyboSoft’s
Nonlinear MFA solutions, click on the following case
Control and Optimization of Crude Oil Separators
Adaptive Control on Fluidized-Bed Boilers
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