000 01892naaaa2200349uu 4500
001 https://directory.doabooks.org/handle/20.500.12854/40109
005 20220220081618.0
020 _aKSP/1000051503
020 _a9783731504672
024 7 _a10.5445/KSP/1000051503
_cdoi
041 0 _aEnglish
042 _adc
100 1 _aSun, Yiming
_4auth
245 1 0 _aAdaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources
260 _bKIT Scientific Publishing
_c2016
300 _a1 electronic resource (XIII, 231 p. p.)
506 0 _aOpen Access
_2star
_fUnrestricted online access
520 _aIn this work, an innovative real-time microwave control approach is proposed, to improve the temperature homogeneity under microwave heating. Multiple adaptive or intelligent control structures have been developed, including the model predictive control, neural network control and reinforcement learning control methods. Experimental results prove that these advanced control methods can effectively reduce the final temperature derivations and improve the temperature homogeneity.
540 _aCreative Commons
_fhttps://creativecommons.org/licenses/by-sa/4.0/
_2cc
_4https://creativecommons.org/licenses/by-sa/4.0/
546 _aEnglish
653 _aBestärkendes Lernenmicrowave heating
653 _aKünstliches neuronales Netz
653 _aMehrgrößenregelung
653 _aMikrowellenerwärmung
653 _amultiple-input multiple-output (MIMO)
653 _aModellprädiktive Regelung
653 _aneural network
653 _amodel predictive control (MPC)
653 _areinforcement learning
856 4 0 _awww.oapen.org
_uhttps://www.ksp.kit.edu/9783731504672
_70
_zDOAB: download the publication
856 4 0 _awww.oapen.org
_uhttps://directory.doabooks.org/handle/20.500.12854/40109
_70
_zDOAB: description of the publication
999 _c75442
_d75442