Computer Applications in Agricultural Environments. Proceedings of Previous Easter Schools in Agricultural Science

297 Pages·1987·9.45 MB·English

by  J.A. Clark

Proceedings of Previous Easter Schools in Agricultural Science, published by Butterworths, London
*SOIL ZOOLOGY Edited by D. K. McL. Kevan (1955)
*THE GROWTH OF LEAVES Edited by F. L. Milthoφe (1956)
•CONTROL OF THE PLANT ENVIRONMENT Edited by J. P. Hudson (1957)
•NUTRITION OF THE LEGUMES Edited by E. G. Hallsworth (1958)
*THE MEASUREMENT OF GRASSLAND PRODUCTIVITY Edited by J. D. Ivins (1959)
•DIGESTIVETPHYSIOLOGY AND NUTRITION OF THE RUMINANT Edited by D. Lewis
(1960)
•NUTRITION OF PIGS AND POULTRY Edited by J. T. Morgan and D. Lewis (1961)
•ANTIBIOTICS IN AGRICULTURE Edited by M. Woodbine (1962)
•THE GROWTH OF THE POTATO Edited by J. D. Ivins and F. L. Milthorpe (1963)
•EXPERIMENTAL PEDOLOGY Edited by E. G. Hallsworth and D. V. Crawford (1964)
•THE GROWTH OF CEREALS AND GRASSES Edited by F. L. Milthorpe and J. D. Ivins (1965)
•REPRODUCTION IN THE FEMALE MAMMAL Edited by G. E. Lamming and E. C. Amoroso
(1967)
•GROWTH AND DEVELOPMENT OF MAMMALS Edited by G. A. Lodge and G. E. Lamming
(1968)
•ROOT GROWTH Edited by W. J. Whittington (1968)
•PROTEINS AS HUMAN FOOD Edited by R. A. Lawrie (1970)
•LACTATION Edited by 1. R. Falconer (1971)
•PIG PRODUCTION Edited by D. J. A. Cole (1972)
•SEED ECOLOGY Edited by W. Heydecker (1973)
HEAT LOSS FROM ANIMALS AND MAN: ASSESSMENT AND CONTROL Edited by J. L.
Monteith and L. E. Mount (1974)
•MEAT Edited by D. J. A. Cole and R. A. Lawrie (1975)
•PRINCIPLES OF CATTLE PRODUCTION Edited by Henry Swan and W. H. Broster (1976)
•LIGHT AND PLANT DEVELOPMENT Edited by H. Smith (1976)
PLANT PROTEINS Edited by G. Norton (1977)
ANTIBIOTICS AND ANTIBIOSIS IN AGRICULTURE Edited by M. Woodbine (1977)
CONTROL OF OVULATION Edited by D. B. Crighton, N. B. Haynes, G. R. Foxcroft and G. E.
Lamming (1978)
POLYSACCHARIDES IN FOOD Edited by J. M. V. Blanshard and J. R. Mitchell (1979)
SEED PRODUCTION Edited by P. D. Hebblethwaite (1980)
PROTEIN DEPOSITION IN ANIMALS Edited by P. J. Buttery and D. B. Lindsay (1981)
PHYSIOLOGICAL PROCESSES LIMITING PLANT PRODUCTIVITY Edited by C. Johnson
(1981)
ENVIRONMENTAL ASPECTS OF HOUSING FOR ANIMAL PRODUCTION Edited by J. A.
Clark (1981)
EFFECTS OF GASEOUS AIR POLLUTION IN AGRICULTURE AND HORTICULTURE
Edited by M. H. Unsworth and D. P. Ormrod (1982)
CHEMICAL MANIPULATION OF CROP GROWTH AND DEVELOPMENT Edited by J. S.
McLaren (1982)
CONTROL OF PIG REPRODUCTION Edited by D. J. A. Cole and G. R. Foxcroft (1982)
SHEEP PRODUCTION Edited by W. Haresign (1983)
UPGRADING WASTE FOR FEEDS AND FOOD Edited by D. A. Ledward, A. J. Taylor and R.
A. Lawrie (1983)
FATS IN ANIMAL NUTRITION Edited by J. Wiseman (1984)
IMMUNOLOGICAL ASPECTS OF REPRODUCTION IN MAMMALS Edited by D.B. Crighton
(1984)
ETHYLENE AND PLANT DEVELOPMENT Edited by J. A. Roberts and G. A. Tucker (1985)
THE PEA CROP Edited by P. D. Hebblethwaite, M. C. Heath and T. C. K. Dawkins (1985)
PLANT TISSUE CULTURE AND ITS AGRICULTURAL APPLICATIONS Edited by Lyndsey
A. Withers and P.G. Alderson (1986)
CONTROL AND MANIPULATION OF ANIMAL GROWTH Edited by P.J. Buttery, D.B.
Lindsay and N.N. Haynes (1986)
• The titles are now out of print but are available in microfiche editions
Computer Applications in
Agricultural Environments
J.A. CLARK
University of Nottingham School of Agriculture
Κ. GREGSON
University of Nottingham School of Agriculture
R.A. SAFFELL
Campbell Scientific Ltd
BUTTERWORTHS
London Boston Durban Singapore Sydney Toronto Wellington
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First published 1987
© The several contributors named in the list of contents 1987
British Library Cataloguing in Publication Data
Computer applications in agricultural environments
1. Agriculture — Data processing
I. Clark, J.Α., 79^6- II. Gregson, Κ.
III. Saffell, R.A.
338.1'6 S494.5.D3
ISBN 0-407-00429-7
Library of Congress Cataloging in Publication Data
Computer applications in agricultural environments.
Proceedings of the 42nd Nottingham Easter School.
Bibliography: p.
Includes index.
1. Greenhouses—Environmental engineering—Data
processing—Congresses. 2. Greenhouses—Climate—Data
processing—Congresses. 3. Animal housing—Environ­
mental engineering—Data processing—Congresses.
4. Animal housing—Climate—Data processing—Congresses.
5. Food industry and trade—Data processing—Congresses.
I. Clark, J.A. (Jeremy Austin), 1938-
II. Gregson, K. III. Saffell, R.A.
SB416.C65 1986 630 86-17121
ISBN 0-407-00429-7
Photoset by Scribe Design, Gillingham, Kent
Printed and bound in Great Britain by Butler and Tanner, Frome, Somerset
PREFACE
The development of the microprocessor has promoted the use of computational
techniques in an expanding variety of applications in measurement and control.
The initial advances in computer control were confined to engineering and related
disciplines, and traditionally the development of computing has occurred within the
pure science and engineering departments of universities and colleges.
The application of computer skills to agriculture has been relatively infrequent,
and until recently has been confined mainly to the economic and managerial aspects
of the farming and food industries. More recently, with the advent of large scale
integrated circuits and the consequent low cost and portability of both computers
and the necessary instrumentation, it has been possible to exploit the power of the
microprocessor outside the laboratory. This has produced a growing awareness that
many of the traditional uses of environmental control mechanisms could benefit
from the application of computers. In particular, the control of the microclimate in
greenhouses and animal houses and for food storage and processing have become
prime areas where the power of the computer may be of benefit.
The aim of this Easter School was to promote this awareness and to provide a
forum where experiences of the application of computer techniques which are
common to many disciplines, but which have been developed and used in a wide
variety of applications, could be shared.
The proceedings of the Easter School may be broken into three main areas. The
first section introduces the theoretical aspects of computer control. This is followed
by examples of applications to the control of the environment of plants in
greenhouses, grain driers, etc. Consideration is also given to the problems
encountered in the food processing industry, illustrating that many of the problems
encountered are not specific to one area of application. The remaining topics of the
conference were in the areas of environmental control for animal housing and data
logging, in which a wide range of computer appHcations were introduced.
A review of the titles and authors of the twenty or so papers presented will reveal
the diversity of the applications and disciplines represented at the conference. This
helped to sustain the discussions both within and outside the formal meetings. The
poster sessions were also a source of many ideas and gave the opportunity for
exchange of opinions.
ACKNOWLEDGEMENTS
We would like to express our thanks to all who presented papers at the meeting and
to those delegates who prepared and presented posters at the evening sessions.
We are also grateful to the Vice-Chancellor of the University, Professor B.C.L.
Weedon, who opened the meeting and extended a welcome to the many overseas
delegates. Thanks are also due to the chairmen of the various sessions, whose skill
ensured good time-keeping throughout the conference.
May we also extend our thanks to Mrs Tricia Falkener Smith who ensured the
smooth running of the meeting and to Mrs Claire Saffell who gave invaluable help
during the conference.
The University of Nottingham School of Agriculture is also grateful to the
following companies who provided financial assistance towards the expenses of the
School:
Seltek Instruments Ltd
Delta-T-Devices Ltd
Grant Instruments Ltd
The Analytical Development Company Ltd
Christie Electronics Ltd
Vector Instruments
Decagon Devices, Inc.
Vaisala UK
Lintronic Ltd
Didcot Instrument Company Ltd
Skye Instruments Ltd
Fisons Environment Equipment Ltd
vn
1
ANALYSIS AND SYNTHESIS OF GREENHOUSE CLIMATE
CONTROLLERS
A.J. UDINKTEN GATE
Agricultural University, Wageningen, Netherlands
Introduction
In Western Europe the popularity of computers for the control of greenhouses is
still increasing. In the Netherlands, for example, computers are found in every
large commercial holding, with about 4000 units in operation. The computer
performs tasks like climate, boiler and irrigation control. The best known
application is climate control (temperature, humidity, CO2, artificial lighting).
Typically, in climate control computer algorithms perform the same functions as
conventional electronic controllers. The main improvements are found in data
logging, the ways in which the set point of a controlled variable can be changed,
reproducibility of the control signals over long periods (no ill-tuned potentio­
meters!) and alarm functions. Also, if a meteorological station is coupled to the
computer some decisions on set point schedules can be made automatically.
Recent trends to energy conservation, as well as the integration of administrative
management and climate control, provide a strong stimulus for improvement of the
quality and accuracy of the cUmate control itself. A computer provides an excellent
tool to employ improved algorithms and new control methods. For analysis and
design purposes there is a great need for models of the greenhouse climate that are
reliable from the control point of view. Also, because of the difficulty of
performing experiments in greenhouses in order to compare the relative merits of
various methods, modelling of the greenhouse climate has become of great
importance.
In contrast to the limited availability of control models of the greenhouse
climate, physical models are widely available. These models are typically of the
aggregated type, where the thermodynamic properties of the greenhouse structure,
the soil and the crop are entered as parameters in a model based on heat and mass
transfer theory. The model can be of the steady state type (e.g. Businger, 1963;
Garzoli and Blackwell, 1973; Kimball, 1973), or can also account for energy storage
in the greenhouse (notably in the soil) (e.g. Takakura, Jordan and Boyd, 1971; Van
Bavel, Damagnez and Sadler, 1981; Bot, 1983). In principle, dynamic physical
models could be employed for control. However, in control the main interest is in
the effect of small perturbations from the nominal working point. As a rule the
perturbations are of relatively high frequency compared with the dominant model
time scale: the working point changes only slowly. So far, physical models have
been used only in simulation runs with slowly varying (low-frequency) input signals,
1
2 Analysis and synthesis of greenhouse climate controllers
whereas the control models must have accurate high-frequency responses with less
stringent requirements on low frequency responses (Udink ten Cate, 1983).
A major reason for the slow development of control models is the relative
complexity of the greenhouse climate. Even for a model of the air temperature
inside a greenhouse, at least four input signals are employed — outside air
temperature, solar radiation, heating system temperature and ventilation rate. This
makes a validation of the model cumbersome. The techniques used in the
validation are time-series analysis (for parameter estimation) and frequency
domain analysis (using Fast Fourier Transform and anti-causal filtering tech
niques). Also, techniques like correlation and power spectrum analysis, which are
based on linear modelling, are used. The above techniques have only become
available quite recently in interactive program packages on minicomputers. The
required amount of data collection is only made possible by using data loggers with
sufficient data storage facilities and by the abiUty to generate test input signals with
the required frequency characteristics. This all explains why control models in
greenhouses have emerged only recently (Hashimoto, Morimoto and Fuñada,
1982; Udink ten Cate and Van de Vooren, 1984; Udink ten Cate, 1985).
The validation of the control models is obtained basically by the reproducibility
of the results under various conditions, which are comparable except for a single
input signal. In enclosed environments like phytotrons this can be achieved by
repeating the same experiment at different times. In a greenhouse, with its many
uncontrollable signals due to weather, validation may be obtained by performing
concurrent experiments in identical compartments (Udink ten Cate, 1983). In the
physical models, validation is achieved by measuring the various sub-processes
accurately in specific experiments. The best way to do this is to model and measure
concurrently the climate of the same greenhouse compartment (Bot, 1983).
Another interesting aspect of the developments in control models is that
development has been impeded by the attitude of researchers to the problem. Even
in the last decade, the underlying philosophy has been to consider greenhouse
computer controllers as operators manipulating various actuators. With the help of
time-clocks and additional measurements the operating requirements can be
transformed into procedures which are carried out by the controller/computer. In
these procedures actuator settings, such as heating system temperature and
ventilation window aperture, are directly related to the (assumed) effects on the
crop. Such procedures may be improved by adding operator knowledge, in terms of
logical decisions and conditional compensations. This type of control is the same as
that found in programmable logical controllers (PLC). Low cost greenhouse
computers operate in this way. However, when the construction of the greenhouse
is such that the control problem is better formulated as dynamic control (in contrast
to static control with a PLC) the resulting performance deteriorates quickly. One of
the intriguing problems of greenhouse climate control is to find a way to combine
the focus on procedures with dynamic control.
It should be mentioned that the term 'control' is generally used in a broad sense,
incorporating static as well as dynamic control. In the perception of an operator,
discontinuous events such as the operation of a thermal screen, or even the
chalking of the glass cover of the greenhouse, are seen as control operations, and
the dynamic nature of the process under control is not analysed. To emphasize the
distinction: when the climate is controlled using continuously operating actuators,
the term greenhouse climate feedback/feed-forward control (GCFFC) is intro
duced (Udink ten Cate, 1982, 1983).
A J, Udinkten Cate 3
Research on climate control reflects the operator's attitude. Relatively few
studies on GCFFC have been published, but even these are restricted to the heating
system control loop (O'Flaherty, Gaffney and Walsh, 1973; Tantau, 1979; Udink
ten Cate and Van de Vooren, 1981; Otto et al., 1982) and the air temperature inside
the greenhouse (Udink ten Cate, 1983, 1985; Udink ten Cate and Van de Vooren,
1984). Experimental estimation of the GCFFC process characteristics using explicit
test signals to perturb the GCFFC model was reported by Udink ten Cate (1983,
1985) and Udink ten Cate and Van de Vooren (1984). Also, Otto et al. (1982) and
O'Flaherty, Gaffney and Walsh (1973) have suggested methods of experimental
data estimation for a GCFFC model (a 'general' model as opposed to a
perturbation model). Udink ten Cate (1983) has clearly demonstrated that a
high-frequency perturbation model has quite different characteristics from a
low-frequency model, which makes a 'general' model, combining low-frequency
plus high-frequency behaviour, more complex than a GCFFC perturbation model
alone.
Recently a 'general' model has been proposed, combining low-frequency and
high-frequency GCFFC behaviour (Udink ten Cate, 1985). In this chapter a new
'general' GCFFC model will be proposed, incorporating the soil of the greenhouse
as a heat storage element. This new model is certainly more elaborate than the
perturbation-type GCFFC model, but is of low complexity when compared with a
physical model, which explains why the word general is placed within inverted
commas. An interesting feature of these models is that they are formulated in terms
of heating-load coefñcients (k-values), which makes them applicable to any
greenhouse.
In addition to GCFFC modelling, attention will be paid to some algorithms
which are employed in the computer control of the heating system/greenhouse air
temperature control loop. Because actuator saturations have a signiñcant impact on
the control loop performance, new performance criteria are established which are
typical for GCFFC. Finally, some improvements in GCFFC are suggested on the
basis of the newly presented 'general' GCFFC model.
Models for GCFFC temperature control
INTRODUCTION
In the field of GCFFC most research has been devoted to the control of the air
temperature inside the greenhouse, because temperature is traditionally considered
to be the most important (and controllable) climate factor. In this chapter two types
of models are presented: the first is a 'general' GCFFC model, incorporating soil
temperature; the second is a perturbation GCFFC model, based not on the
'general' model, which is the usual mathematically oriented approach, but on a
reduced greenhouse representation, which is the typical engineering approach.
Being based on different assumptions, validation of the parameters of the two
models leads to different values. A new approach combining the perturbation
model and the 'general' model will also be presented. The perturbation model is
described in detail by Udink ten Cate (1983) and the combination of the 'general'
model with the perturbation model by Udink ten Cate (1985), while the 'general'
model has not been published before.
4 Analysis and synthesis of greenhouse climate controllers
THE 'GENERAL' GCFFC MODEL
Figure 1.1 depicts a greenhouse and the actuators that are commonly used in
GCFFC. Inside the greenhouse the air temperature 6g (°C) is regulated by heating
and ventilation. The cHmate inside the greenhouse depends on the outside weather
conditions, such as ambient air temperature 6a (°C), wind velocity v^^ (ms~^), wind
direction, incident short-wave (solar) radiation (W) and long-wave radiation φι
(W). Recent research in GCFFC modelling has indicated that the soil temperature
also plays an important role. The soil heat storage is represented by a single layer
with soil temperature 65 (°C) and at greater depth a constant soil temperature
rc).
Bsc
Figure 1.1 Greenhouse climate control
The greenhouse is heated by a system consisting of a heating network in which
water is circulated, usually by 51mm pipes. The inlet temperature of the pipe
network is (°C) and that of the outlet or return water temperature is (°C),
leading to an average heating system temperature of θπ (°C). The water inlet
temperature is obtained by mixing return water with feedwater (from a main) of
temperature 9f (°C), in a three-way mixing valve with position r^ (0-100%).
Ventilation is achieved by the opening and closing of ventilation windows; the
aperture is r^ (0-100%), leading to an air exchange rate of (m^s"^). The
variable is, as a rule, replaced by the ventilation rate (or air change rate) 5v (h"^)
which is the number of air exchanges per hour per greenhouse
36009ν(ί) (1.1)
5v(i) =
where (m^) is the greenhouse air volume. In an average greenhouse with single
glass cladding will be in the range 0.5-10 in winter conditions. In summer 5v can
be up to 100.
The dynamic behaviour of the GCFFC loops can be represented in a convenient
way by the introduction of incremental variables. These increments lead to a
perturbation model. For example, the increment θ(ί) of a temperature 0(r) is
defined by
0(0 = 6(0-0 (1.2)
The average, 0, describes the working point for the equilibrium situation which in
principle is constant, but can also vary slowly in time.
A J. Udinkten Cate 5
I ^S'^s ,
Figure 1.2 The greenhouse as a perfectly stirred tank
The 'general' model of the greenhouse temperature is based upon the
approximation of a greenhouse as a perfectly stirred tank (Figure 1,2).
Considering Figure 1.2 and assuming uniform variables leads to the following
equations.
C g3 = q,{t) Cp ρ(θ^(ί) - θ^(ί)) +¿(eh(í) - θ^(/)) + (θβίΟ - θ^(ί)) +
4-(Θ3(ί)-θ8(ί)) + ηφ»(0 (l-3a)
and
^=-^m) - m) + (Öse - m) (1.3b)
Cs
where Cg is the greenhouse inside heat capacity (J K"^) (composed of values for air
and construction parts); Cp — 10^ J kg"^ K"^ is the specific heat of dry air at constant
pressure; ρ — 1.2kgm"^ is the air density; Äh, RT-, RSC (K W~^) are the thermal
resistances of the heating system, the roof and side walls, the first layer of the soil,
and the second layer of the soil, respectively; and η is the fraction of solar radiation
absorbed. Note that in Equations 1.3α,ο only convection or conduction heat ñuxes
are represented explicitly. Long-wave radiation heat exchange from the
greenhouse roof to the sky and latent heat exchange are not taken into account.
This is justified because these effects are incorporated in the way the values of the
thermal resistances are obtained in practice, though this will lead to short-term
errors in the GCFFC model. The fraction η indicates the conversion of solar
radiation into sensible heat, and is significantly different from the greenhouse roof
transmissivity.
Equations 1.3αφ are normalized in terms of units of ground area. If the ground
area of the greenhouse is A^ (m^), the normalized parameters are as follows:
C* ^ C,/A„, C* ^ CJA, (J m-2); qt(t) ^ q.{t)IA¿, kl ^ l/(i?h^g); A:? ^
\l{RrA^)\ kl ^ l/(/?s^g); and Ä:*c = ll{Rs<A^) (W m'^ K"^).
From Equation 1.1 it follows that
36ÖÖ