Adaptive systems in control and signal processing, 1989 : by Michael A Johnson; International Federation of Automatic

By Michael A Johnson; International Federation of Automatic Control

The Symposium lined 3 significant parts: adaptive keep an eye on, id and sign processing. In all 3, new advancements have been mentioned masking either theoretical and functions examine. in the topic quarter of adaptive keep watch over the dialogue concentrated round the demanding situations of strong keep an eye on layout to unmodelled dynamics, powerful parameter estimation and more desirable functionality from the estimator, whereas the papers on identity took the topic of it being a bridge among adaptive keep an eye on and sign processing. the ultimate region checked out features of sign processing: recursive estimation and adaptive filters.

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Extra resources for Adaptive systems in control and signal processing, 1989 : selected papers from the 3rd IFAC Symposium, Glasgow, UK, 19-21 April 1989

Example text

N and l: are real non-negative definite weighting matrices. Thus, the design problem is to minimise the cost (5) subject to the constraint that the closed-loop system defined by equations ( 1 )-(4) be asymptotically stable. 3. e. that there exist stable polynomial matrices De, Df and G (the 39 l l D ( i [ P, Q ,R , S] = [XD fb - i , Y D r a- , M o 2 - , (17) (YD ra- 1 c a - Z)Ac - 1 cs - 1 AJ Here, X and Y (along with V) is the solution of the equations: spectral factors) which satisfy: (7) ( 1 8 a) (8) such that =O.

An adapUve control algorithm solving an underlying con­ trol problem thali coincides with the semiinfinite LQ stochas­ tic feedback has been developed. , T � n + 1, n being the order of the ARMAX plant, together with an appropriate control synthesis rule. The propOled algorithm. turns out to be a slighily modified ver­ sion of MUSMAR with the capability of tuning itself to the semiinfinite horilOll LQ stochastic regulator (LQSR). In­ deed, ii is shown that, in the abeence of unmodelled plant dynamics, the LQSR feedback ill an equilibrium point of the resulting algorithm, denominated MUSMAR-oo.

Sternad 34 3-10 iterations. The coupled equations (6),(7) represent an over-determined set of simultaneous equations in the coeffi­ cients of R, S and X. The system will however have a unique solution with the polynomial degrees (9). ) This (exact) solution can be found by computing the least-squares solution to the overdetermined system. Step 6. The servo filter T/E has been designed by can­ celling poles and stable zeros so that a reference model Ym(t) = (q-k Bm/Am)r(t) is approximated. This works well, but results in a rather high-order filter.

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