In the synthesis of the control algorithm for complex systems, we are
often faced with imprecise or unknown mathematical models of the dynamical
systems, or even with problems in finding a mathematical model of the system in
the open loop. To tackle these difficulties, an approach of data-driven model
identification and control algorithm design based on the maximum stability
degree criterion is proposed in this paper. The data-driven model
identification procedure supposes the finding of the mathematical model of the
system based on the undamped transient response of the closed-loop system. The
system is approximated with theinertial
model, where the coefficients are calculated based on the values of the
critical transfer coefficient, oscillation
amplitude and period of the underdamped response of the closed-loop
system. The data driven control design supposes that the tuning parameters of
the controller are calculated based on the parameters obtained from the
previous step of system identification and there are presented the expressions
for the calculation of the tuning parameters. The obtained results of data-driven model
identification and algorithm for synthesis the controller were verified by
computer simulation.
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