describing function

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describing function

[di′skrīb·iŋ ‚fəŋk·shən]
(control systems)
A function used to represent a nonlinear transfer function by an approximately equivalent linear transfer function; it is the ratio of the phasor representing the fundamental component of the output of the nonlinearity, determined by Fourier analysis, to the phasor representing a sinusoidal input signal.
McGraw-Hill Dictionary of Scientific & Technical Terms, 6E, Copyright © 2003 by The McGraw-Hill Companies, Inc.
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Substituting dependences (16) and (17) to the general solution, described with formula (1), upon double integration, gives a dependence describing function of bending of the analysed converter (18):
Nonlinear controller's syntheses using inverse describing function for use with hard nonlinear system have developed for several researchers [11-13].
Karimi, "Nonlinear controller synthesis based on inverse describing function technique in the MATLAB environment," Advances in Engineering Software, vol.
Jonckheere, "[H.sub.[infinity]] control of a class of nonlinear systems using describing functions and simplicial algorithms," IEEE Transactions on Automatic Control, vol.
A detailed describing function analysis for theoretical support of the controller gain change method.
A theoretical justification through describing function analysis is also presented.
In this section, describing function analysis is used to provide a theoretical justification for the observed closed-loop behaviour due to changes in controller gain.
Hinkle (2001) provides results describing function during acute care following a motor stroke in more detail.
Working hierarchically from most important information to the least, Anthony describes Bi-design, overall processing flows and network browsers, network site servers, server processing reorganization, and progresses to his system of derived simplicity, describing function set network representation, database representation, data relationship management and a dream language.
It systematically analyzes several fuzzy proportional-integral-derivative (PID) control systems and state space control and also takes on self-learning control mechanisms while covering fuzzy reasoning, fuzzy control, linear and non-linear fuzzy PID control, stability analysis by describing functions, and supervisory control.

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