Trends in Modeling and Sensing Approaches for Drying Control

REFERENCES

• Mujumdar , A.S. Principles, classification and selection of dryers . In Handbook of Industrial Drying ; Mujumdar , A.S. , Ed.; Taylor & Francis Group : Boca Raton , FL , 2006 ; 3 – 32 .
   Google Scholar
• Jumah , R.Y. ; Mujumdar , A.S. ; Raghavan , V.G.S. Control of industrial dryers . In Handbook of Industrial Drying ; Mujumdar , A.S. , Ed.; Taylor & Francis Group : Boca Raton , FL , 2006 ; 1161 – 1181 .
   Google Scholar
• Iguaz , A. ; Budman , H. ; Douglas , P.L. Modelling and control of an alfalfa rotary dryer . Drying Technology 2002 , 20 ( 9 ), 1869 – 1877 .
   Web of Science ®Google Scholar
• Ryniecki , A. ; Nellist , M.E. Optimization of control systems for near ambient grain drying: Part 1, The optimization procedure . Journal of Agricultural Engineering Research 1991 , 48 , 1 – 17 .
   Web of Science ®Google Scholar
• Dufour , P. Control engineering in drying technology: review and trends . Drying Technology 2006 , 24 , 889 – 904 .
   Web of Science ®Google Scholar
• Corrêa , N.A. ; Freire , J.T. ; Corrêa , R.G. Improving operability of spouted beds using a simple optimizing control structure . Brazilian Journal of Chemical Engineering 1999 , 16 ( 4 ), 359 – 368 .
   Web of Science ®Google Scholar
• Bi , H. A critical review of the complex pressure fluctuation phenomenon in gas–solid fluidized beds . Chemical Engineering Science 2007 , 62 , 3473 – 3493 .
   Web of Science ®Google Scholar
• van Ommen , J.R. ; Sasic , S. ; van der Schaff , J. ; Gheorgiu , S. ; Johnsson , F. ; Coppens , M.-O. Time-series analysis of pressure fluctuations in gas–solid fluidized beds—A review . International Journal of Multiphase Flow 2011 , 37 , 403 – 428 .
   Web of Science ®Google Scholar
• Kang , W.K. ; Sutherland , J.P. ; Osberg , G.L. Pressure fluctuations in a fluidized bed with and without screen cylindrical packings . Industrial and Engineering Chemistry Fundamentals 1967 , 6 ( 4 ), 499 – 504 .
   Web of Science ®Google Scholar
• Prata , A.S. ; Maudhuit , A. ; Boillereaux , L. ; Poncelet , D. Development of a control system to anticipate agglomeration in fluidised bed coating . Powder Technology 2012 , 224 , 168 – 174 .
   Web of Science ®Google Scholar
• Parise , M.R. ; Silva , C.A.M. ; Ramazini , M.J. ; Taranto , O.P. Identification of defluidization in fluidized bed coating using the Gaussian spectral pressure distribution . Powder Technology 2011 , 206 , 149 – 153 .
   Web of Science ®Google Scholar
• Silva , C.A.M. ; Parise , M.R. ; Silva , F.V. ; Taranto , O.P. Control of fluidized bed coating particles using Gaussian spectral pressure distribution . Powder Technology 2011 , 212 , 445 – 458 .
   Web of Science ®Google Scholar
• Xu , J. ; Bao , X. ; Wei , W. ; Shi , G. ; Shen , S. ; Bi , H.T. ; Grace , J.R. ; Lim , C.H. Statistical and frequency analysis of pressure fluctuations in spouted beds . Powder Technology 2004 , 140 , 141 – 154 .
   Web of Science ®Google Scholar
• Butzge , J.J. ; Silva , C.A.M. ; Taranto , O.P. Spectral analysis: A contribution to control strategy on spouted bed . Chemical Engineering Transactions 2013 , 32 , 2197 – 2202 .
   Google Scholar
• Lopes , N.E.C. ; Moris , V.A.S. ; Taranto , O.P. Analysis of spouted bed pressure fluctuations during particle coating . Chemical Engineering and Processing 2009 , 48 , 1129 – 1134 .
   Web of Science ®Google Scholar
• Lee , J.S. ; Chang , K.S. Analysis of chaos and fractals in process systems engineering . Journal of Process Control 1996 , 6 ( 2–3 ), 71 – 87 .
   Web of Science ®Google Scholar
• Johnsson , F. ; Zijerveld , R.C. ; Schouten , J.C. ; van den Bleek , C.M. ; Leckner , B. Characterization of fluidization regimes by time-series analysis of pressure fluctuations . International Journal of Multiphase Flow 2000 , 26 , 663 – 715 .
   Web of Science ®Google Scholar
• Sprott , J.C. Chaos and Time-Series Analysis ; Oxford University Press : Oxford , UK , 2006 .
   Google Scholar
• Castilho , G.J. ; Cremasco , M.A. Study of gas–solids flow in a short CFB riser by statistical and chaotic deterministic analysis of optical fibre probe signals . Canadian Journal of Chemical Engineering 2013 , 91 , 579 – 588 .
   Web of Science ®Google Scholar
• Vervloet , D. ; Nijenhuis , J. ; van Ommen , J.R. Monitoring a lab-scale fluidized bed dryer: A comparison between pressure transducers, passive acoustic emissions and vibration measurements . Powder Technology 2010 , 197 , 36 – 48 .
   Web of Science ®Google Scholar
• Boyd , J.W.D. ; Varley , J. The uses of passive measurement of acoustic emissions from chemical engineering processes . Chemical Engineering Science 2001 , 56 , 1749 – 1767 .
   Web of Science ®Google Scholar
• McClements , J. Ultrasonic characterization of foods and drinks: Principles, methods, and applications . Critical Reviews in Food Science and Nutrition 1997 , 37 , 1 – 46 .
   PubMed Web of Science ®Google Scholar
• Mulet , A. ; Benedito , J. ; Golás , Y. ; Cárcel , J.A. Noninvasive ultrasonic measurements in the food industry . Critical Reviews in Food Science and Nutrition 2002 , 18 ( 2–3 ), 123 – 133 .
   Google Scholar
• Briens , L. ; Bojarra , M. Monitoring fluidized bed drying of pharmaceutical granules . AAPS PharmSciTech 2010 , 11 ( 4 ), 1612 – 1618 .
   PubMed Web of Science ®Google Scholar
• Jumah , R. ; Mujumdar , A.S. Modeling intermittent drying using an adaptive neuro-fuzzy inference system . Drying Technology 2005 , 23 , 1075 – 1092 .
   Web of Science ®Google Scholar
• Yliniemi , L. ; Koskinen , J. ; Leiviskä , K. Data-driven fuzzy modelling of a rotary dryer . International Journal of Systems Science 2003 , 34 ( 14 & 15 ), 819 – 836 .
   Web of Science ®Google Scholar
• Raghavan , G.S.V. ; Li , Z. ; Wang , N. ; Gariépy , Y. Control of microwave drying process through aroma monitoring . Drying Technology 2010 , 28 , 591 – 599 .
   Web of Science ®Google Scholar
• Teunou , E. ; Fitzpatrick , J.J. ; Synnott , E.C. Characterisation of food powder flowability . Journal of Food Engineering 1999 , 39 , 31 – 37 .
   Web of Science ®Google Scholar
• Corrêa , N.A. ; Freire , F.B. ; Corrêa , R.G. ; Freire , J.T. Comparison among PI, DMC, QDMC, and GPC algorithms in the control of the spouted bed dryer . Chemical engineering Communications 2006 , 193 , 24 – 37 .
   Web of Science ®Google Scholar
• Block , B. ; Lipták , B.G. ; Shinskey , F.G. Dryer controls . In Instrument Engineers’ Handbook: Process Control and Optimization ; Lipták , B.G. , Ed.; CRC Press : Boca Raton , FL , 2006 ; 1904 – 1913 .
   Google Scholar
• Brodgesell , A. ; Lipták , B.G. Moisture in solids . In Instrument Engineers’ Handbook: Process Measurement and Analysis ; Lipták , B.G. , Ed.; CRC Press : Boca Raton , FL , 2006 ; 1450 – 1456 .
   Google Scholar
• Carr-Brion , K. Moisture Sensors in Process Control ; Elsevier Science : London , 1986 .
   Google Scholar
• Stawczyk , J. ; Muñoz , I. ; Collell , C. ; Comaposada , J. Control system for sausage drying based on on-line NIW a w determination . Drying Technology 2009 , 27 , 1338 – 1343 .
   Web of Science ®Google Scholar
• Kadlec , P. ; Gabrys , B. ; Strandt , S. Data-driven soft sensors in the process industry . Computers and Chemical Engineering 2009 , 33 , 795 – 814 .
   Web of Science ®Google Scholar
• Kadlec , P. ; Grbcic , R. ; Gabrys , B. Review of adaptation mechanisms for data-driven soft sensors . Computers and Chemical Engineering 2011 , 35 , 1 – 24 .
   Web of Science ®Google Scholar
• Briens , L. ; Smith , R. ; Briens , C. Monitoring of a rotary dryer using acoustic emissions . Powder Technology 2008 , 181 , 115 – 120 .
   Web of Science ®Google Scholar
• Jensen , S. ; Meleiro , L.A.C. ; Zanoelo , E.F. Soft-sensor model design for control of a virtual conveyor-belt dryer of mate leaves (Ilex paraguariensis). Biosystems Engineering 2011, 108, 75–85.
   Web of Science ®Google Scholar
• Shahhosseini , S. ; Cameron , I.T. ; Wang , F.Y. A dynamic model with on-line identification for rotary sugar drying processes . Drying Technology 2001 , 19 , 2103 – 2129 .
   Web of Science ®Google Scholar
• Himmelblau , D.M. Accounts of experiences in the application of artificial neural networks in chemical engineering . Industrial and Chemical Engineering Research 2008 , 47 , 5782 – 5796 .
   Web of Science ®Google Scholar
• Farkas , I. Use of artificial intelligence for the modelling of drying processes . Drying Technology 2013 , 31 , 848 – 855 .
   Web of Science ®Google Scholar
• Freire , J.T. ; Freire , F.B. ; Ferreira , M.C. ; Nascimento , B.S. A hybrid lumped parameter/neural network model for spouted bed drying of pastes with inert particles . Drying Technology 2011 , 30 ( 11–12 ), 1342 – 1353 .
   Web of Science ®Google Scholar
• Cubillos , F.A. ; Vyhmeister , E. ; Acuña , G. ; Alvarez , P.I. Rotary dryer control using a grey-box neural model scheme . Drying Technology 2011 , 29 , 1820 – 1827 .
   Web of Science ®Google Scholar
• Köni , M. ; Yüzgeç , U. ; Türker , M. ; Dinçer , H. Adaptive neuro-fuzzy-based control of drying of baker's yeast in batch fluidized bed . Drying Technology 2010 , 28 , 205 – 213 .
   Web of Science ®Google Scholar
• Velardi , S.A. ; Hammouri , H. ; Barresi , A.A. Development of a high-gain observer for in-line monitoring of sublimation in vial freeze drying . Drying Technology 2010 , 28 , 256 – 268 .
   Web of Science ®Google Scholar
• Velardi , S.A. ; Hammouri , H. ; Barresi , A.A. In-line monitoring of the primary drying phase of the freeze-drying process in vial by means of a Kalman filter based observer . Chemical Engineering Research and Design 2009 , 87 , 1409 – 1419 .
   Web of Science ®Google Scholar