Performance analysis of robust stable PID controllers using dominant pole placement for SOPTD process models
Das, S; Halder, K; Gupta, A
Date: 31 January 2018
Article
Journal
Knowledge-Based Systems
Publisher
Elsevier
Publisher DOI
Abstract
This paper derives new formulations for designing dominant pole placement based proportionalintegral-derivative
(PID) controllers to handle second order processes with time delays (SOPTD).
Previously, similar attempts have been made for pole placement in delay-free systems. The presence
of the time delay term manifests itself as a ...
This paper derives new formulations for designing dominant pole placement based proportionalintegral-derivative
(PID) controllers to handle second order processes with time delays (SOPTD).
Previously, similar attempts have been made for pole placement in delay-free systems. The presence
of the time delay term manifests itself as a higher order system with variable number of interlaced
poles and zeros upon Pade approximation, which makes it difficult to achieve precise pole placement
control. We here report the analytical expressions to constrain the closed loop dominant and nondominant
poles at the desired locations in the complex s-plane, using a third order Pade
approximation for the delay term. However, invariance of the closed loop performance with different
time delay approximation has also been verified using increasing order of Pade, representing a closed
to reality higher order delay dynamics. The choice of the nature of non-dominant poles e.g. all being
complex, real or a combination of them modifies the characteristic equation and influences the
achievable stability regions. The effect of different types of non-dominant poles and the
corresponding stability regions are obtained for nine test-bench processes indicating different levels of
open-loop damping and lag to delay ratio. Next, we investigate which expression yields a wider
stability region in the design parameter space by using Monte Carlo simulations while uniformly
sampling a chosen design parameter space. The accepted data-points from the stabilizing region in the
design parameter space can then be mapped on to the PID controller parameter space, relating these
two sets of parameters. The widest stability region is then used to find out the most robust solution
which are investigated using an unsupervised data clustering algorithm yielding the optimal centroid
location of the arbitrary shaped stability regions. Various time and frequency domain control
performance parameters are investigated next, as well as their deviations with uncertain process
parameters, using thousands of Monte Carlo simulations, around the robust stable solution for each of
the nine test-bench processes. We also report, PID controller tuning rules for the robust stable
solutions using the test-bench processes while also providing computational complexity analysis of
the algorithm and carry out hypothesis testing for the distribution of sampled data-points for different
classes of process dynamics and non-dominant pole types.
Mathematics and Statistics
Faculty of Environment, Science and Economy
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