By Professor I. D. Landau, Professor R. Lozano, Professor M. M’Saad (auth.)
Adaptive Control presents suggestions for computerized, real-time alterations in controller parameters so one can reaching and/or preserving a fascinating point of process functionality within the presence of unknown or variable method parameters.
Many points of the sphere are handled in coherent and orderly type, beginning with the issues posed by means of procedure uncertainties and relocating directly to the presentation of suggestions and their functional importance. in the normal context of modern advancements, the publication appears to be like at:
• synthesis and research of parameter model algorithms;
• recursive plant-model identity in open and closed loop;
• powerful electronic regulate for adaptive control;
• direct and oblique adaptive regulate; and
• sensible elements and applications.
To mirror the significance of electronic pcs for the appliance of adaptive keep watch over thoughts, discrete-time elements are emphasised. to steer the reader, the booklet includes a number of functions of adaptive keep watch over techniques.
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Additional info for Adaptive Control
3. 6 : Indirect adaptive contro l (detailed scheme) model has to b e est imate d is no t ri ch enoug h (meaning a sufficiently large frequen cy sp ectrum ). Using t he indirect adapt ive con trol sche me s shown in Fig. 6, on e ca n further ela b orate on the ad-hoc use of t he "certainty equivalence " or "sepa rat ion t heore m" whi ch hold for t he linear ca se with known paramet ers . In te rms of separati on it is ass umed that t he adaptive predictor gives a good predi ction (or estima tion ) of t he plant output (or states) when t he plant parameter s a re unknown , a nd t hat the prediction erro r is indep enden t of the input to the pl ant (this is fal se how ever during adaptation t ransients) .
1. The adaptat ion mech anism in t his case is a sim ple lookup t able st ored in t he com puter whi ch gives the cont roller pa ramet ers for a given set of envir onme nt measurem ents. This technique ass umes the existence of a rigid relationsh ip between some measurable va riables characterizing t he environme nt (the op er ating conditions) and t he parameter s of t he pl ant model. Using t his re lations hip, it is t he n po ssible to reduce (or t o eliminate) t he effect of pa ramet er va riation s upon t he pe rformance of t he system by changing t he pa ramet ers of the cont roller acc ording ly.
37) is obtained . Subtracting Eq. 37) from Eq. 41) is obtained . Since on e takes ad va nt a ge of Eq. 1. 7). The orders of pol ynomials E j (q- l) and Fj (q- l) assur e t he unicit y of the solu tions of Eq. (2. 41). Eq. 45) ' P n A, P n A+ l " ' PnA +j- l ] + j ) X (n A + j ). 1). On e repl aces: fj (t + j - 1) = f[y (t + j - 2) · · ·J, t hen fj (t + j - 2) = f [y(t + j - 3) · · ·] and so on . 40 2. D iscr et e T im e Sy st em Models for Control Regressor form Taking into acc ount the form of Eq.
Adaptive Control by Professor I. D. Landau, Professor R. Lozano, Professor M. M’Saad (auth.)