51. Fernandes S, Richelle A, Amribt Z, Dewasme L, Bogaerts P, Wouwer AV (2015) Extended and
unscented Kalman filter design for hybridoma cell fed-batch and continuous cultures. IFACPapers 48(8):1108–1113
52. Dewasme L, Fernandes S, Amribt Z, Santos LO, Bogaerts P, Wouwer AV (2015) State
estimation and predictive control of fed-batch cultures of hybridoma cells. J Process Control
30:50–57
53. Zhao L, Wang J, Yu T, Chen K, Liu T (2015) Nonlinear state estimation for fermentation
process using cubature Kalman filter to incorporate delayed measurements. Chin J Chem Eng
23(11):1801–1810
54. Krämer D, King R (2016) On-line monitoring of substrates and biomass using near-infrared
spectroscopy and model-based state estimation for enzyme production by S. cerevisiae. IFACPapers 49(7):609–614
55. Simutis R, Lübbert A (2017) Hybrid approach to state estimation for bioprocess control.
Bioengineering 4(1):21
56. Krishna VV, Pappa N, Rani SJV (2018) Implementation of embedded soft sensor for bioreactor
on Zynq processing system. In: 2018 international conference on recent trends in electrical,
control and communication (RTECC), IEEE
57. Krämer D, King R (2019) A hybrid approach for bioprocess state estimation using NIR
spectroscopy and a sigma-point Kalman filter. J Process Control 82:91–104
58. Ritschel TK, Boiroux D, Nielsen MK, Huusom JK, Jørgensen SB, Jørgensen JB (2019) The
extended Kalman filter for nonlinear state estimation in a U-loop bioreactor. In: 2019 IEEE
conference on control technology and applications (CCTA), IEEE
59. Feidl F, Garbellini S, Luna MF, Vogg S, Souquet J, Broly H, Butté A (2019) Combining
mechanistic modeling and Raman spectroscopy for monitoring antibody chromatographic
purification. PRO 7(10):683
60. Lisci S, Grosso M, Tronci S (2020) A geometric observer-assisted approach to tailor state
estimation in a bioreactor for ethanol production. PRO 8(4):480
61. Sonnleitner B (2013) Automated measurement and monitoring of bioprocesses: key elements of
the M 3 C strategy. In: Measurement, monitoring, modelling and control of bioprocesses.
Springer, Berlin, pp 1–33
62. Biechele P, Busse C, Solle D, Scheper T, Reardon K (2015) Sensor systems for bioprocess
monitoring. Eng Life Sci 15(5):469–488
63. Vojinović V, Cabral JMS, Fonseca LP (2006) Real-time bioprocess monitoring: part I: in situ
sensors. Sensors Actuators B Chem 114(2):1083–1091
64. Chhatre S (2012) Modelling approaches for bio-manufacturing operations. In: Measurement,
monitoring, modelling and control of bioprocesses. Springer, Berlin, pp 85–107
65. Monod J (1949) The growth of bacterial cultures. Annu Rev Microbiol 3(1):371–394
66. Henson MA, Seborg DE (1992) Nonlinear control strategies for continuous fermenters. Chem
Eng Sci 47(4):821–835
67. Jones KD, Kompala DS (1999) Cybernetic model of the growth dynamics of Saccharomyces
cerevisiae in batch and continuous cultures. J Biotechnol 71(1–3):105–131
69. Contois DE (1959) Kinetics of bacterial growth: relationship between population density and
specific growth rate of continuous cultures. Microbiology 21(1):40–50
69. Yousefi-Darani A, Paquet-Durand O, Babor M, Hitzmann B (2020) Model-based calibration of
a gas sensor array for on-line monitoring of ethanol concentration in Saccharomyces cerevisiae
batch cultivation. Biosyst Eng 198(2020):198–209
70. Galvanauskas V, Simutis R, Levišauskas D, Urniežius R (2019) Practical solutions for specific
growth rate control systems in industrial bioreactors. PRO 7(10):693
71. Oisiovici RM, Cruz SL (2000) State estimation of batch distillation columns using an extended
Kalman filter. Chem Eng Sci 55(20):4667–4680
72. Hashemi R, Engell S (2016) Effect of sampling rate on the divergence of the extended Kalman
filter for a continuous polymerization reactor in comparison with particle filtering. IFAC-Papers
49(7):365–370
The Kalman Filter for the Supervision of Cultivation Processes
125
unscented Kalman filter design for hybridoma cell fed-batch and continuous cultures. IFACPapers 48(8):1108–1113
52. Dewasme L, Fernandes S, Amribt Z, Santos LO, Bogaerts P, Wouwer AV (2015) State
estimation and predictive control of fed-batch cultures of hybridoma cells. J Process Control
30:50–57
53. Zhao L, Wang J, Yu T, Chen K, Liu T (2015) Nonlinear state estimation for fermentation
process using cubature Kalman filter to incorporate delayed measurements. Chin J Chem Eng
23(11):1801–1810
54. Krämer D, King R (2016) On-line monitoring of substrates and biomass using near-infrared
spectroscopy and model-based state estimation for enzyme production by S. cerevisiae. IFACPapers 49(7):609–614
55. Simutis R, Lübbert A (2017) Hybrid approach to state estimation for bioprocess control.
Bioengineering 4(1):21
56. Krishna VV, Pappa N, Rani SJV (2018) Implementation of embedded soft sensor for bioreactor
on Zynq processing system. In: 2018 international conference on recent trends in electrical,
control and communication (RTECC), IEEE
57. Krämer D, King R (2019) A hybrid approach for bioprocess state estimation using NIR
spectroscopy and a sigma-point Kalman filter. J Process Control 82:91–104
58. Ritschel TK, Boiroux D, Nielsen MK, Huusom JK, Jørgensen SB, Jørgensen JB (2019) The
extended Kalman filter for nonlinear state estimation in a U-loop bioreactor. In: 2019 IEEE
conference on control technology and applications (CCTA), IEEE
59. Feidl F, Garbellini S, Luna MF, Vogg S, Souquet J, Broly H, Butté A (2019) Combining
mechanistic modeling and Raman spectroscopy for monitoring antibody chromatographic
purification. PRO 7(10):683
60. Lisci S, Grosso M, Tronci S (2020) A geometric observer-assisted approach to tailor state
estimation in a bioreactor for ethanol production. PRO 8(4):480
61. Sonnleitner B (2013) Automated measurement and monitoring of bioprocesses: key elements of
the M 3 C strategy. In: Measurement, monitoring, modelling and control of bioprocesses.
Springer, Berlin, pp 1–33
62. Biechele P, Busse C, Solle D, Scheper T, Reardon K (2015) Sensor systems for bioprocess
monitoring. Eng Life Sci 15(5):469–488
63. Vojinović V, Cabral JMS, Fonseca LP (2006) Real-time bioprocess monitoring: part I: in situ
sensors. Sensors Actuators B Chem 114(2):1083–1091
64. Chhatre S (2012) Modelling approaches for bio-manufacturing operations. In: Measurement,
monitoring, modelling and control of bioprocesses. Springer, Berlin, pp 85–107
65. Monod J (1949) The growth of bacterial cultures. Annu Rev Microbiol 3(1):371–394
66. Henson MA, Seborg DE (1992) Nonlinear control strategies for continuous fermenters. Chem
Eng Sci 47(4):821–835
67. Jones KD, Kompala DS (1999) Cybernetic model of the growth dynamics of Saccharomyces
cerevisiae in batch and continuous cultures. J Biotechnol 71(1–3):105–131
69. Contois DE (1959) Kinetics of bacterial growth: relationship between population density and
specific growth rate of continuous cultures. Microbiology 21(1):40–50
69. Yousefi-Darani A, Paquet-Durand O, Babor M, Hitzmann B (2020) Model-based calibration of
a gas sensor array for on-line monitoring of ethanol concentration in Saccharomyces cerevisiae
batch cultivation. Biosyst Eng 198(2020):198–209
70. Galvanauskas V, Simutis R, Levišauskas D, Urniežius R (2019) Practical solutions for specific
growth rate control systems in industrial bioreactors. PRO 7(10):693
71. Oisiovici RM, Cruz SL (2000) State estimation of batch distillation columns using an extended
Kalman filter. Chem Eng Sci 55(20):4667–4680
72. Hashemi R, Engell S (2016) Effect of sampling rate on the divergence of the extended Kalman
filter for a continuous polymerization reactor in comparison with particle filtering. IFAC-Papers
49(7):365–370
The Kalman Filter for the Supervision of Cultivation Processes
125