By Professor I. D. Landau, Professor R. Lozano, Professor M. M’Saad (auth.)
Adaptive Control offers suggestions for computerized, real-time changes in controller parameters in order to attaining and/or holding a fascinating point of procedure functionality within the presence of unknown or variable method parameters.
Many features of the sphere are handled in coherent and orderly model, beginning with the issues posed by way of approach uncertainties and relocating directly to the presentation of ideas and their sensible value. in the normal context of contemporary advancements, the booklet appears at:
• synthesis and research of parameter model algorithms;
• recursive plant-model id in open and closed loop;
• strong electronic keep watch over for adaptive control;
• direct and oblique adaptive keep an eye on; and
• useful points and applications.
To replicate the significance of electronic pcs for the applying of adaptive keep an eye on strategies, discrete-time features are emphasised. to lead the reader, the e-book comprises numerous purposes of adaptive keep an eye on techniques.
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Extra info for Adaptive Control
F~ F ' g1 ... gnB+j-1] ¢T (t ) = [y(t) · · ·y(t - n F) , u( t + j - d -1) · · · u (t + j - 2d - nB)] G j (q- 1) -- Ei- B * -- go + g1q- 1 .. 51) Stochastic Environment Input-Output Models In many practical sit uations, the det erministic input-output model given in Eq. 1) ca nnot t ak e into acc ount the presen ce of st ochast ic disturban ces. A model is t herefore need ed whi ch acc ommodates t he presen ce of such di sturbances. 1) wh er e v (t ) is a stochas t ic process which describes t he effect upon the ou tput of t he various st ochast ic di sturban ces.
Ie( . . f~ F ' g1 ... gnB+j-1] ¢T (t ) = [y(t) · · ·y(t - n F) , u( t + j - d -1) · · · u (t + j - 2d - nB)] G j (q- 1) -- Ei- B * -- go + g1q- 1 .. 51) Stochastic Environment Input-Output Models In many practical sit uations, the det erministic input-output model given in Eq. 1) ca nnot t ak e into acc ount the presen ce of st ochast ic disturban ces. A model is t herefore need ed whi ch acc ommodates t he presen ce of such di sturbances. 1) wh er e v (t ) is a stochas t ic process which describes t he effect upon the ou tput of t he various st ochast ic di sturban ces.
An horizon ofquire n B samples (delayed d samples). 1) ca n b e ers more represented ct ably in t imeor . 3) cons ide re d sim plified linea r models nonlinea(q-1 r systems tion condit ion will lead to a different line a rized model) . These sit uat ions m ay also Using the notations: oc cur sim ply b ecause the paramet ers of the sys te m are slowly time-va ry ing (in a wiring machine the iner nA ti a of the sp ool is time-varyin g) . 4) wh en large a nd unknown chang ; = 1 es in model parameters occur, a n adaptive control a pproach has to be considered.