Adaptive control tutorial by Petros Ioannou, Barýp Fidan

By Petros Ioannou, Barýp Fidan

Designed to fulfill the wishes of a large viewers with no sacrificing mathematical intensity and rigor, Adaptive keep watch over educational provides the layout, research, and alertness of a large choice of algorithms that may be used to control dynamical platforms with unknown parameters. Its tutorial-style presentation of the basic thoughts and algorithms in adaptive regulate make it compatible as a textbook.

Adaptive keep an eye on educational is designed to serve the desires of 3 specific teams of readers: engineers and scholars attracted to studying how one can layout, simulate, and enforce parameter estimators and adaptive keep an eye on schemes with no need to completely comprehend the analytical and technical proofs; graduate scholars who, as well as reaching the aforementioned ambitions, additionally are looking to comprehend the research of easy schemes and get an concept of the stairs desirous about extra advanced proofs; and complicated scholars and researchers who are looking to research and comprehend the main points of lengthy and technical proofs with a watch towards pursuing learn in adaptive keep an eye on or similar subject matters.

The authors in attaining those a number of pursuits by means of enriching the booklet with examples demonstrating the layout strategies and simple research steps and by way of detailing their proofs in either an appendix and electronically to be had supplementary fabric; on-line examples also are on hand. an answer handbook for teachers should be bought through contacting SIAM or the authors.

This publication may be important to masters- and Ph.D.-level scholars in addition to electric, mechanical, and aerospace engineers and utilized mathematicians.

Preface; Acknowledgements; record of Acronyms; bankruptcy 1: creation; bankruptcy 2: Parametric types; bankruptcy three: Parameter identity: non-stop Time; bankruptcy four: Parameter id: Discrete Time; bankruptcy five: Continuous-Time version Reference Adaptive keep an eye on; bankruptcy 6: Continuous-Time Adaptive Pole Placement keep watch over; bankruptcy 7: Adaptive keep watch over for Discrete-Time structures;

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Example text

31). At each time t, J (9) is a convex function of 0 and therefore has a global minimum. The gradient algorithm takes the form where F = YT > 0 is a design matrix referred to as the adaptive gain. 29) constitute the gradient parameter identification algorithm based on the instantaneous cost function whose stability properties are given by the following theorem. 1. v, 0 e £2 H £00 and 9 e £00. 0* exponentially fast. In addition, where 0 < / < nTg, n — 0, 1, 2, . . , it consists of at least "+"'+l distinct frequencies, then 0, ^- are PE.

5. Example: Vector Case 35 where If Z(s) is Hurwitz, a bilinear model can be obtained as follows: Consider the polynomials P(s) — pn-\sn~{ + • • • + p\s + PQ, Q(s) = s"~] + qn-2sn~2 + • • • + q\s + qo which satisfy the Diophantine equation (see the Appendix) where A 0 (^) is a monic Hurwitz polynomial of order 2n — m — 1. v) 0 Letting we obtain the B-SPM We should note that in this case 6* contains not the coefficients of the plant transfer function but the coefficients of the polynomials P(s), Q(s).

Since 0* is a constant vector, the DPM may be written as where 0 = L~l(s)\fs, L(s) is chosen so that L~' (5) is a proper stable transfer function, and W(s)L(s) is a proper strictly positive real (SPR) transfer function. We form the normalized estimation error where the static normalizing signal ns is designed so that ^- e £00 for m2s = 1 + n]. 50) has the same expression as in the case of the gradient algorithm.

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