Notes

The PID filter is implemented
in almost all industrial processes because of its well‐
known beneficial features. In general, the whole system’s
performance strongly depends on the controller’s
efficiency and hence the tuning process plays a key role
in the system’s behaviour

Nevertheless, this method
can be improved by integrating an optimization
technique

When designing
control systems in the industry, approximately 95 percent
of these systems are Proportional‐Integral‐Derivative
(PID) controllers [3] and 85 percent of these are
implemented on closed‐loop systems with a single input
and a single output configuration [4]. The reasons for the
wide use of these controllers are the easiness of their implementation in digital systems, their robustness, low
cost maintenance, and so on

y in parameter optimization is the application of
the GA due to their powerful searching capabilities and
heuristic characteristics

PID controller tuned at a particular operating point will not
provide a satisfying response when there exists deviation in
the process operating range

s exhibits typical nonlinear and time varying
behaviour where control of the parameter reactor concentration with few computation steps is a challenge to the
researchers. Therefore, it becomes essential to use powerful
heuristic algorithms like GA to tune the PID parameters,
thereby achieving good set point tracking and disturbance
rejection control in the chemical system CSTR


The self-organizing GA optimization
method has been used for evolving PID controller parameters
to avoid premature convergence and to achieve good optimization performance