State Detection and Feedback Control of the Anaerobic Wastewater Treatment Using Fuzzy Logic

160 Pages·2002·1.32 MB·English

Lehrstuhl für Fluidmechanik und Prozeßautomation
der Technischen Universität München
State Detection and Feedback Control of the
Anaerobic Wastewater Treatment Using Fuzzy Logic
Ernst Murnleitner
Vollständiger Abdruck der von der Fakultät Wissenschaftszentrum Weihenstephan
für Ernährung, Landnutzung und Umwelt der Technischen Universität München zur
Erlangung des akademischen Grades eines
Doktor-Ingenieurs (Dr.-Ing.)
genehmigten Dissertation.
Vorsitzender: Univ.-Prof. Dr.-Ing. K. Sommer
Prüfer der Dissertation: 1. Univ.-Prof. Dr.-Ing. habil. Antonio Delgado
2. Univ.-Prof. Dr.-Ing. Roland Meyer-Pittroff
3. Univ.-Prof. Dr.-Ing., Dr. h.c. Peter A.Wilderer
Die Dissertation wurde am 22. 11. 2001 bei der Technischen Universität München
eingereicht und durch die Fakultät Wissenschaftszentrum Weihenstephan für
Ernährung, Landnutzung und Umwelt am 21. 12. 2001 angenommen.
II
This thesis was published with the same title in the series
15, number 237 of the “VDI Fortschrittsberichte” (VDI
proceedings) by VDI Verlag, Düsseldorf.
ISBN 3-18-323715-6
III
A
CKNOWLEDGEMENTS
This thesis was made from 1997 to 2001 at the “Lehrstuhl für Fluidmechanik und
Prozessautomation” at the “Technische Universität München”. My thank goes to all,
who have supported me in this time.
Especially, I wish to thank my “Doktorvater” Prof. Dr.-Ing. Antonio Delgado, who
made this work possible and who allowed me wide academic freedom. I also want to
thank Dr.-Ing. Thomas Becker for the productive discussions and disputes. He also
developed the core of the fuzzy logic system, which was used as basis in this work. I
had also a lot of productive discussions with my colleague, Dipl.-Ing. Tomas Kurz.
I also wish to thank Walter Seidl and Sepp Rohrer who supported me in
construction of the pilot plant, as well as Hans Bauer and Ralph Schmidt, who
supported me in electrical affairs.
The pH controllers presented in this work follow directly from the master thesis of
Dipl.-Ing. Tobias König. I also thank him for assistance in the PLC programming.
Special thank goes to Dipl.-Ing. Martin Grepmeier for cooperation in the
experiments and for the COD analytics. I also wish to thank Dr.-Ing. Uwe Behmel,
who suggested the controlling of a biogas plant by the use of Fuzzy logic.
I wish to thank Nicole Weber for the correction concerning the English language.
Further, I wish to thank Prof. Dr.-Ing. Meier-Pittroff and Prof. Dr.-Ing., Dr. hc.
Peter Wilderer for their interest in my work and for their audit, as well as Prof. Dr.-
Ing. Karl Sommer for taking the chair of the examination board.
This work would not have been possible without the knowledge about modelling,
which I learned from Prof. Dr.ir. Sef Heijnen and Prof. Dr.ir. Mark van Loosdrecht at
the Technical University Delft in the course of my master thesis.
Parts of this work were supported by the Bayerische Forschungsstiftung (AZ
216/96).
Last, but not least, I wish to thank all my colleagues at the LFP for the friendly
climate I could experience there.
Freising, December 2001 Ernst Murnleitner
IV
Meinen Eltern gewidmet.
For my parents.
V
T C
ABLE OF ONTENTS
Acknowledgements_________________________________________________ III
Table of Contents ___________________________________________________ V
Nomenclature ____________________________________________________VIII
Units__________________________________________________________VIII
Appreviations __________________________________________________VIII
Symbols ________________________________________________________ IX
Subscripts for Flows_______________________________________________ X
Subscripts for Balances ___________________________________________ XI
Abstract_________________________________________________________ XII
Zusammenfassung ________________________________________________ XIV
Publications _____________________________________________________ XVI
1 Introduction and Conceptional Formulation___________________________ 1
1.1 Initial Situation_______________________________________________ 1
1.2 State of the Art _______________________________________________ 3
1.3 The Scope of the Thesis ________________________________________ 4
1.4 Reference to Other Theses______________________________________ 5
2 Relevant Aspects with Regard to the Thesis____________________________ 6
2.1 Microbial Considerations ______________________________________ 6
2.1.1 Hydrolysis and Acidogenesis __________________________________ 8
2.1.2 Acetogenesis and Methanogenesis_____________________________ 11
2.1.3 Sulphate Reducing Bacteria __________________________________ 13
2.1.4 Temperature and pH value ___________________________________ 13
2.2 Process engineering aspects____________________________________ 15
2.2.1 One or Two Stage Process ___________________________________ 15
2.2.2 Reactor types _____________________________________________ 16
2.3 Control Aspects _____________________________________________ 17
2.3.1 pH Control _______________________________________________ 18
2.3.2 Alternative Control Methods _________________________________ 19
2.3.3 Fuzzy Rulebase____________________________________________ 20
2.4 Experimental Setup __________________________________________ 25
3 Presentation and Discussion of the Results___________________________ 28
VI
3.1 Overall Concept _____________________________________________ 28
3.1.1 Sequential Controls and Subcontrollers on the PLC________________ 29
3.1.2 Tasks on the PC ___________________________________________ 39
3.1.3 Conclusions ______________________________________________ 40
3.2 Development of the gas measurement system _____________________ 41
3.2.1 Choice of Sensors__________________________________________ 42
3.2.2 Integration of the Sensors____________________________________ 43
3.2.3 Validation of the Gas Test System _____________________________ 44
3.2.4 Conclusions ______________________________________________ 46
3.3 Development of the pH Controllers _____________________________ 46
3.3.1 Requirements for the pH controllers____________________________ 46
3.3.2 Adaptive Controller for the Acidificaton Buffer Tank ______________ 47
3.3.3 PID Controller for the Methane Reactor_________________________ 51
3.3.4 Conclusions ______________________________________________ 53
3.4 Development of the Fuzzy Logic Expert System ___________________ 54
3.4.1 Structure of the Fuzzy System ________________________________ 54
3.4.2 Input values ______________________________________________ 60
3.4.3 Fermentation states_________________________________________ 61
3.4.4 Global strategies___________________________________________ 63
3.4.5 Output values _____________________________________________ 63
3.4.6 Conclusions ______________________________________________ 64
3.5 Experimental Validation of the Whole System ____________________ 65
3.5.1 Conclusions ______________________________________________ 73
3.6 Modelling and Simulation _____________________________________ 73
3.6.1 Requirements for the Simulation Model_________________________ 73
3.6.2 Existing Models ___________________________________________ 74
3.6.3 General Strategy and Choice of Base Models ____________________ 75
3.6.4 Development and Details of the Model _________________________ 77
3.6.5 Validation of the Model _____________________________________ 96
3.6.6 Conclusions _____________________________________________ 102
3.7 Validation by Simulation_____________________________________ 103
3.7.1 Simulation of the Overload Experiment________________________ 103
3.7.2 Prediction of More Extreme Process Variations__________________ 107
3.7.3 Conclusions _____________________________________________ 110
4 Conclusions and Outlook ________________________________________ 111
5 Materials and Methods__________________________________________ 112
5.1 Reactor ___________________________________________________ 112
5.2 Fixed Bed _________________________________________________ 114
VII
5.3 Analytical Methods _________________________________________ 114
5.4 Experiments and Simulations _________________________________ 115
5.4.1 Experiment E0 ___________________________________________ 115
5.4.2 Experiments E1, E2, E3 ____________________________________ 115
5.4.3 Simulations S0, S1 and Substrate Peaks________________________ 115
5.4.4 Experiments K5, K7 and Simulations SK5, SK7 _________________ 116
5.5 Online-Measurements and Data Logging________________________ 116
5.5.1 Calibration ______________________________________________ 116
5.5.2 Measurement Value Processing and Logging____________________ 117
5.6 Implementation of the Human Machine Interface ________________ 117
5.7 Implementation of the Fuzzy Logic Software ____________________ 118
5.7.1 Rule parser ______________________________________________ 119
5.7.2 Fuzzy inference __________________________________________ 120
5.8 Implementation and Tuning of the Controllers___________________ 122
5.8.1 Adaptive pH Controller for the Acidification Buffer Tank__________ 122
5.8.2 PID Controller for the pH of the Methane Reactor________________ 123
5.8.3 PID Controllers for the Temperature __________________________ 124
Appendix________________________________________________________ 126
Derivation of the modified PID controller ___________________________ 126
Additional Figures ______________________________________________ 127
Simulation of pH-Step Function-Response of the Methane Reactor ______ 130
Investigations about Replacement Methods for TOC or COD___________ 131
Conductivity, pH and Volatile Fatty Acid Concentrations ______________ 133
Conversion of units______________________________________________ 136
Volatile Fatty Acid Concentrations of Experiment E0 _________________ 137
References_______________________________________________________ 138
VIII
N
OMENCLATURE
Units
If not mentioned otherwise, SI units are used, except for time and temperature
where h and °C are used.
Gas concentrations in % or ppm are meant as volume/volume.
Appreviations
A/D analoguetodigital conversion
AF anaerobicfilterreactor(fixed bed reactor)
ANN artificial neural net
ATP adenosin triphosphate
BOD biological oxygen demand (5days)
5
C1 chemical orbiological reactor1=acidification reactor
C2 chemical orbiological reactor2=methanereactor
COD chemical oxygen demand
COG centerof gravity
CSTR continuous stirred tank reactor(ideallymixed reactor)
D/A digital toanalogueconvertion
DC directcurrent
DLL dynamiclink library(compiled computercode)
FB function block
FBBR fluidised bed biofilmreactor
Fd ferredoxin,oxydised
FdH ferredoxin,reduced
HMI human/machineinterface
KOP ladderdiagram(Kontaktplan)
IC internal circuitreactor
IL instruction list
LAD,LD ladderdiagram
MO microorganism(s)
NAD nicotinamideadeninedinucleotide,oxydised
NADH nicotinamideadeninedinucleotide,reduced
2
OLE objectlinkingand embedding(adataexchangemethod)
ORP oxido/reductivopotential
P&ID pipingand installation diagram
PC personal computer
PCS process control system
PFR plugflow reactor
PD proportional – differential controller
PI proportional –integral controller
PID proportional –integral –differential controller
PLC programmablelogiccontroller
IX
QF liquid testpoint forqualitymeasurands
QG gas testpointforqualitymeasureands
RIP rulebased interpolation controller
SAK spectral absorbancecoefficient
STL instruction list(statementlist)
TOC total organiccarbon
UASB upflow anaerobicsludgebed reactor
Symbols
a specificsurface m²m-³
A surface m²
C total concentration of componenti mol m-³
i
C total concentration of componenti in compartmentc mol m-³
i,c
C concentration of componenti in theinflow mol m-³
in,i
C initial concentration of componenti mol m-³
ini,i
C concentration of componenti in theinflow of compartmentc mol m-³
in,i,c
C initial concentration of componenti in compartmentc mol m-³
ini,i,c
C concentration of componenti degradingbacteria mol m-³
X,i
C concentration of componenti degradingbacteriain inflow mol m-³
X,in,i
C initial concentration of componenti degradingbacteria mol m-³
X,ini,i
D diffusion coefficientof componenti in thebiofilmmatrix m²h-1
f,i
d hydraulicdiameter m
h
D diffusion coefficientof componenti in water m²h-1
i
d decay/maintenancerateforcomponenti degradingbacteria h-1
X,i
e controll deviation
f pH dependencyfunction
pH,i
f factorforrelativepuffercapacity(pH controller)
puffer
f temperaturedependencyterm
T
h reactorliquid level (fraction of fillinglevel tofull volume)
H heightof reactorliquid level m
H partition coefficientaccordingtohenry's law
i
I non-competitiveinhibition term
j
I inhibition termforpH >7includingammoniatoxicity
nh4,pH
K dissociation constantof componenti mol m-³
a,i
k kineticconstantfordegradation of componenti mol mol-1 h-1
i
K half inhibition concentration of componentjon the mol m-³
I,i,j
degradation of componenti
k liquid togas mass transfercoefficient mh-1
Lg,i
k liquid tosolid mass transfercoefficient mh-1
Ls,i
K Monod half velocityconstantof componenti mol m-³
i
K proportional action coefficient(forPIDcontroller)
p
K’ proportional action coefficient,normalized forflow and mol h m-2
p
concentration
K ion productof water mol m-³
w
L length m
M monod substratelimitation term
i
MI substratelimitation termof componenti with competitive
i,j
X
inhibition of componentj
p absolutepressure bar
pH pH value
pH actual pH value
act
∆∆∆∆pH expected increaseof pH valueduetocontrol action
inc
pH pH value,wheremaximumgrowth occurs
m
pH lowerpH value,whereinhibion is total
l
p partial pressureof componenti bar
i
Q waterorgas flow m³h-1
Re dimensionless Reynold numberusingthehydraulicdiameter
h
s thickness m
Sc dimensionless Schmidtnumberforcomponenti
i
Sh dimensionless Sherwood number
t time h
T temperature °C
T integral action timeforPI and PIDcontroller h
n
T dead time h
u
T derivativeaction timeforPDand PIDcontroller h
v
u hydraulicvelocity mh-1
V volumeof liquid (plus bed)in thereactororcompartment m³
V& circulation rate m³h-1
V amountof lyewhich is added in apH control action m³
lye_abs
V amountof lyewhich is needed toincreasepH of full reactor m³
lye_rel
for1unitfromcurrentpH value
Y yield enzymepercomponenti mol mol-1
e,i
Y yield biomass percomponenti mol mol-1
i
z term,used forhydrogen inhibition
h2
z term,used forhydrogen inhibition
h2factor
α enzymesaturation constantfordegradation of componenti mol m-³
i
νννν kinematicviscosity h m-2
∆
G0’ reaction enthalpyatpH 7,25°Cand molarconcentrations. Jmol-1
∅∅∅∅ diameter m
∅∅∅∅ innerdiameter m
i
∅∅∅∅ outerdiameter m
o
Subscripts for Flows
1 acidification buffertank
2 methanereactor
circ circulation
G head spaceof reactor
L lyevessel
l lowercompartment
m mediumcompartment
O outsidereactors
u uppercompartment