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4.2. IntelligentControl
Plant
(HEPHAISTOS)
NN Controller
NN Estimator
Target
Temperature Measured
Temperature
Control
Input
Estimated
Dynamics
Figure4.6. Semi-direct control structure. The blue dashed line represents two
possible learningapproaches.
The main advantage of the semi-direct control structure is that the
overall weight update of the NN controller is significantly acceler-
ated. The average weight update rate can be increased to once per
control period or even higher. In addition, there is no extra waiting
time spent on the states or outputs recovery. The NN controller us-
ing one-measurement SPSA learning can quickly evolve from the ini-
tialized state to a nearly optimal state, which guarantees acceptable
control performance in the starting period. Defining the modulo op-
erationas
r= Mod(a,n) =a−nba
n c, for a,n,r∈R,
wherer is thereminderofadividedbyn.
The complete procedures of the semi-direct control scheme is shown
infigure 4.7.
4.2. IntelligentControl
Intelligent control is a class of control methods that utilize ideas and
approaches from the artificial intelligence or biological systems to
solve the control problem [WSF94]. Technically, both aforementioned
nonlinear GA control and NNC methods can be classified as intelli-
gent control approaches. Nevertheless, in this dissertation intelligent
107
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
- Mikrowellenerwärmung, Mehrgrößenregelung, Modellprädiktive Regelung, Künstliches neuronales Netz, Bestärkendes Lernenmicrowave heating, multiple-input multiple-output (MIMO), model predictive control (MPC), neural network, reinforcement learning
- Kategorie
- Technik