Pk. Viswanathan et al., Closed-loop identification of TITO processes using time-domain curve fitting and genetic algorithms, IND ENG RES, 40(13), 2001, pp. 2818-2826
Closed-loop identification of two-input two-output (TITO) processes by time
-domain curve fitting to minimize the sum of the squared errors between the
actual and calculated closed-loop responses is studied. The perceived diff
iculties with this methodology are the need for global optimization because
of the possible existence of multiple minima, the extensive computations,
the evaluation of numerical derivatives for efficient optimization methods,
and the accuracy and reliability of the results. In this study, a genetic
algorithm (GA) is employed to locate reliably the global minimum of the lea
st-squares problem. Results show that time-domain curve fitting via GA, fol
lowed by the BFGS method, recovers accurate and reliable transfer function
models of TITO processes from closed-loop responses under a range of test c
onditions including different controller settings in the closed-loop test,
different durations of the test, underdamped or overdamped closed-loop resp
onses, and measurement noise. Because closed-loop tests need not be conduct
ed until steady state is reached, the test duration can be reduced signific
antly.