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4.1. AdaptiveControl
QDMCcontainstwomainsteps. Thefirststepistoapplythestandard
DMCtothecontroltaskandobtainacontrolsolution. Ifthecontrolso-
lutionfulfills the inputconstraint (asgivenbyequation 4.4), itwillbe
directlyusedasthetruecontrolsolutionU(k). Otherwiseif itdoesnot
fulfill the input constraint, a new quadratic programming (QP) prob-
lem [GM86] has to be formulated and another control solution will be
calculated. ProceduresofQDMCaregiven in the following.
Instandardtime-invariantDMC,thelineardiscrete-timeequation3.41
isfirstlyre-written inacompletestate-space formas[Wan09]
X(k+1) = [A(k)]X(k)+[B(k)]U(k),
Y(k) = X(k), (4.7)
where X(k) is the state variable vector. Defining the difference state,
inputandoutputvectorsas
âX(k) =X(k)âX(kâ1),
âU(k) =U(k)âU(kâ1),
âY(k) =Y(k)âY(kâ1),
there is
âX(k+1) = X(k+1)âX(k) = [A(k)]âX(k)+[B(k)]âU(k).
(4.8)
In order to simplify notations during following derivations, new aug-
mentedmatricesaredefinedas [Wan09]
Xd(k) = [
âX(k)
Y(k) ]
, [Ad(k)] = [
[A(k)] [ON]
[A(k)] [IN] ]
,
[Bd(k)] = [
[B(k)]
[B(k)] ]
, [Cd(k)] = [
[ON] [IN] ]
,
where [ON]and [IN]arezeroandidentitymatrices (NĂN).
Substituting above new defined matrices into equation 4.8, a new
state-space formedsystemmodel isgeneratedas
Xd(k+1) = [Ad(k)]Xd(k)+[Bd(k)]âU(k),
Y(k) = [Cd(k)]Xd(k) (4.9)
91
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Buch Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources"
Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
- Titel
- Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
- Autor
- Yiming Sun
- Verlag
- KIT Scientific Publishing
- Ort
- Karlsruhe
- Datum
- 2016
- Sprache
- englisch
- Lizenz
- CC BY-SA 3.0
- ISBN
- 978-3-7315-0467-2
- Abmessungen
- 14.8 x 21.0 cm
- Seiten
- 260
- Schlagwörter
- MikrowellenerwĂ€rmung, MehrgröĂenregelung, ModellprĂ€diktive Regelung, KĂŒnstliches neuronales Netz, BestĂ€rkendes Lernenmicrowave heating, multiple-input multiple-output (MIMO), model predictive control (MPC), neural network, reinforcement learning
- Kategorie
- Technik