Quadratic Model-Based Dynamically Updated PID Control of CSTR System with Varying Parameters
Journal
Algorithms
Date Issued
2021-01
Author(s)
Stavrov, Dusko
Nadzinski, Gorjan
Deskovski, Stojche
DOI
https://doi.org/ 10.3390/a14020031
Abstract
In this paper, we discuss an improved version of the conventional PID (Proportional–
Integral–Derivative) controller, the Dynamically Updated PID (DUPID) controller. The DUPID is a
control solution which preserves the advantages of the PID controller and tends to improve them
by introducing a quadratic error model in the PID control structure. The quadratic error model
is constructed over a window of past error points. The objective is to use the model to give the
conventional PID controller the awareness needed to battle the effects caused by the variation of
the parameters. The quality of the predictions that the model is able to deliver depends on the
appropriate selection of data used for its construction. In this regard, the paper discusses two
algorithms, named 1D (one dimensional) and 2D (two dimensional) DUPID. Appropriate to their
names, the former selects data based on one coordinate, whereas the latter selects the data based
on two coordinates. Both these versions of the DUPID controller are compared to the conventional
PID controller with respect to their capabilities of controlling a Continuous Stirred Tank Reactor
(CSTR) system with varying parameters in three different scenarios. As a quantifying measure of
the control performance, the integral of absolute error (IAE) metric is used. The results from the
performed simulations indicated that the two versions of the DUPID controller improved the control
performance of the conventional PID controller in all scenarios.
Integral–Derivative) controller, the Dynamically Updated PID (DUPID) controller. The DUPID is a
control solution which preserves the advantages of the PID controller and tends to improve them
by introducing a quadratic error model in the PID control structure. The quadratic error model
is constructed over a window of past error points. The objective is to use the model to give the
conventional PID controller the awareness needed to battle the effects caused by the variation of
the parameters. The quality of the predictions that the model is able to deliver depends on the
appropriate selection of data used for its construction. In this regard, the paper discusses two
algorithms, named 1D (one dimensional) and 2D (two dimensional) DUPID. Appropriate to their
names, the former selects data based on one coordinate, whereas the latter selects the data based
on two coordinates. Both these versions of the DUPID controller are compared to the conventional
PID controller with respect to their capabilities of controlling a Continuous Stirred Tank Reactor
(CSTR) system with varying parameters in three different scenarios. As a quantifying measure of
the control performance, the integral of absolute error (IAE) metric is used. The results from the
performed simulations indicated that the two versions of the DUPID controller improved the control
performance of the conventional PID controller in all scenarios.
Subjects
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