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A distributed system for glasshouse climate control, data acquisition and analysis
Computers and Electronics in Agriculture, 3 (1988) 1-9 Elsevier Science Publishers B.V., Amsterdam - - Printed in The Netherlands
1
A distributed System for Glasshouse Climate Control, Data Acquisition and Analysis J.C. BAKKER, L. VAN DEN BOS, A.J. ARENDZEN and L. SPAANS
Glasshouse Crops Research Station (GCRS), P.O. Box 8, 2670 AA Naaldwijk (The Netherlands) (Accepted 17 February 1988)
ABSTRACT Bakker, J.C., Van den Bos, L., Arendzen, A.J. and Spaans, J., 1988. A distributed system for glasshouse climate control, data acquisition and analysis. Comput. Electron. Agric., 3: 1-9. To cope with future developments in glasshouse climate control, a distributed computer system is installed at the GCRS. The hard- and software of the system are described. The system has four types of computers networked together by Ethernet. It controls and collects data from eight glasshouse blocks with over 70 different compartments. The advantages of this system are: reliability, speed, flexibility, easy servicing, user-friendliness and easy expansibility.
I NTRODUCTION
In 1974 a Siemens 330 process computer was installed at the GCRS in Naaldwijk to control the climate in a 24-compartment glasshouse (Van de Vooren, 1975 ). Since then the number of computer-controlled glasshouse compartments has gradually increased. After 13 years of successful use the Siemens 330 system has been replaced by a new distributed system to cope with future developments in glasshouse climate control. The knowledge about physical processes (Bot, 1983; Stanghellini, 1987) and control processes in the glasshouse (Udink ten Care, 1983; Tantau, 1985), together with plant-growth models (Nederhoff and Schapendonk, 1985) will form the basis for new environmental control procedures. Within the next 10 years new control procedures, based on economic optimization of production (Challa et al., 1980), are expected. The climate-control system needs, therefore, besides simple control procedures (comparable to those available to growers), the possibility of using large simulation-based optimization control procedures. Furthermore, interdependent control of glasshouse and root environment is expected in the near future. To cope with these requirements the system should be reliable, fast, flexible, easily expansible, user-friendly, and have a large memory capacity. In this report the hard- and software of the new system are described, to0168-1699/88/$03.50
© 1988 Elsevier Science Publishers B.V.
gether with recent developments in glasshouse climate control and future research at the GCRS. SYSTEM COMPONENTS AND DATA ACQUISITION
The system is set up with three levels of computer systems linked by a local area network (Ethernet, IEEE 802.3) (Fig. 1). Ethernet is an IEEE standard developed in cooperation between Xerox, Intel and Digital. The signals are Manchester-encoded digital signals, the communication protocol is based on the CSMA/CD technique, and the transport speed is 10 Mbits s- 1. A detailed description of Ethernet is given by Van Keulen and Oostindjer (1986). The lowest-level micro (level 0), situated near the glasshouse, measures physical data: temperature, humidity, C02 and light, and controls pipe temperatures, ventilation windows, thermal screens, CO2 dosing valves and supplementary lighting. Each micro controls up to three different pipe-heating systems, wind- and leeward (roof) ventilation, two thermal screens, a COz valve (pure CO2 or from natural-gas combustion) and supplementary lighting in three to ten different glasshouse compartments, depending on the required I/O. One level-0 micro is used for measurement of outside weather conditions (temperature, direct and diffuse radiation, PAR, windspeed and direction, humidity, rainfall, sunshine and COe). Details of the different sensors are listed in Table 1.
~ - -
LAN (ETHERNET)
Fig. 1. Outline of the distributed system for glasshouse climate control and data acquisition: DA, data acquisition system; DELNI, local area network interconnect; LAN, local are network; TS, terminal server (DEC server 100 or 200).
TABLE1 Sensors~rclimatemeasurementsinsideandoutsidetheglasshouses Temperature
Humidity
Temperature/Humidity (outside) CO~ Radiation: Global Diffuse PAR
Net Sunshine Windspeed/direction Rainfall
4-wire RTD (Pt-100) DIN 43760 copper-constantan thermocouples (only in combination with KAYE or Acurex data acquisition systems ) aspirated dry-wet bulb psychrometers with RTD (made by the Technical Physical Service for Agriculture, TFDL, in Wageningen ) THIES Clima MZTI 7Z50, + 2~ Siemens IRGA ZFDSC, 0-3000 ppm, +_1% Siemens IRGA Ultramat P22, 0-5000 ppm, + lC'i Kipp & Zonen Solarimeter C M l l . 305-2800 nm Kipp & Zonen Solarimeter CMll/121, both _+3% TFDL light sensor 21903.4,400 700 nm, _+5% BWD Industries LTD, Net Pyrradiometer CN1, ~_3~ HAENNI Solar 110 THIES Clima 43296.0.3-40 in s t 0 360= on/off: Wilhelm Lambrecht KGHP 1515 THIES Clima 540310, max 2 mm h - '. +_3%
At the GCRS, two types of computers are used at level 0, a Siemens Siematic $5-210B system and an INCAA system. The Siemens $5-210B has an 8-bit 3M H z SAB 8085 processor, 5 Kbytes of RAM, and 20 Kbytes E P R O M . It measures up to 256 input channels. The INCAA system has an 8-bit Motorola 6800 processor, 2 Kbytes of RAM, 4 Kbytes E P R O M and measures up to 128 input channels. Both systems measure RTDs (4-wire Pt-100) and mV (0-100 mV) signals with a sample time of 20 s. Each level 0 micro is connected to the LAN by a RS-232C interface, a terminal server (DEC-server 100, DSRVA-AB) and a D E L N I (Local Network Interconnect ). The level 1 system is a MicroVAX II 630 QB system with a 32-bit processor. It has 4 Mbytes of R A M and 144 Mbytes of hard-disk storage. On this computer, the control programmes ( F O R T R A N 77) are running with a cycle time of 1 min. The environmental data and calculated setpoints are stored every minute in a direct-access file for a maximum of 4 days. The level 2 is a VAX-750 superminicomputer with a 32-bit processor and 5 Mbytes of RAM, 460 Mbytes of hard disk storage and a TU-80 tape unit. All data collected at level 1 can be transferred to level 2 for statistical analysis and long-term storage. This system is also used, in an interactive programming mode, to develop growth and production models of glasshouse crops. The level 1 and 2 micros are connected to the LAN by a DELNI. For intensive measurements in glasshouse compartments, data acquisition
systems are used (KAYE dig;strip III and Acurex Autocalc). These systems can measure RTDs, mV and high-voltage signals, different types of thermocouples, and digital inputs. Both systems can be connected to the LAN by a patch-panel and a terminal server (Fig. 1), or operate stand-alone and store the data on cassette tape (Cristie CS 7, cassette terminal). For presentation of environmental data, results of statistical analysis and simulation studies, four tally matrix dot printers and an HP 7550 graphics plotter are available. Since all computers are networked together, researchers can check the performance of the control system and change setpoints at each of the 20 terminals connected. At this moment; eleven level 0 micros are installed, controlling eight glasshouse blocks with over 70 different compartments. About 2200 physical data and setpoints are stored every minute on the level 1 system. CONTROL SOFTWAREAND DATAHANDLING
Standard climate control programmes and alarm procedures The standard control programmes are able to control temperature (three different pipe-heating systems per compartment, and ventilation), CO2 enrichment (pure C02 or from natural-gas combustion), two thermal screens, and supplementary lighting. The heating system is controlled by the dog-lead algorithm (Udink ten Cate, 1983); ventilation and the thermal screens are proportionally controlled, CO2 by a PI controller. Setpoints for heating and ventilation and minimum settings of pipe temperature and ventilation can be influenced according to outside conditions. Thermal screens can be used for energy saving or shading and can also be influenced according to outside conditions. The routine to calculate proportions is a renewed version of the one described by Van de Vooren and Strijbosch (1979). For temperature control and thermal screens, four different setpoints can be programmed over a period of 24 h; for CO2 enrichment and root heating, two periods are available. The different periods can be related to absolute time or to sunrise and sunset. All setpoints can be used as fixed setpoints or, depending on outside or inside conditions, as presented in Table 2. For temperature control, an extra control procedure is added by which temperature can be controlled at a 24-h mean setpoint. In this procedure the setpoint for the night temperature is calculated on-line, depending on the temperature integral received and the remaining night-length (De Koning, 1988). The VAX-750 has simple control procedures which are activated automatically to take over the temperature control in all glasshouses in the event the level-1 system fails. If both levels 1 and 2 fail, the level 0 continues control at
TABLE 2 Standard control procedures Setpoints
Number of Depending on periods Outside conditions
Inside conditions
radiation wind temperature temperature humidity Heating Setpoint Minimum pipe Maximum pipe Root heating Ventilation Setpoint temperature Setpoint humidity Minimum window Maximum window Thermal screen Setpoint CO~ enrichment Supplementary lighting on/off
4 4 4 2
fixed setpoint watertemperature
4 4 4 1
+ + -
+ +
+ +
4 2 2
+ + +
+ +h -
+ _ -
+
+
+
-
+
+
m
"Setpoint corrected on line to maintain a 24-h average temperature. ~Depending on ventilation rate. the s e t p o i n t s last received. A ' w a t c h - d o g ' triggers a n a l a r m s y s t e m if level 1 or level 2 fails. F u r t h e r m o r e , e a c h level 0 c a n trigger t h e a l a r m s y s t e m in t h e e v e n t this m i c r o or t h e c o m m u n i c a t i o n fails, or if t h e g l a s s h o u s e t e m p e r a t u r e in one of the c o m p a r t m e n t s is b e y o n d t h e a l a r m limits ( t h e s e limits c a n be c h a n g e d by an interactive programme). A l a r m m e s s a g e s are p r i n t e d a n d ( d u r i n g t h e nights a n d w e e k e n d s ) a p h o necall is m a d e to w a r n t h e t e c h n i c a l service a n d o p e r a t o r . E a c h day a list of all n o n - f u n c t i o n i n g s e n s o r s is p r i n t e d .
Performance of the standard temperature and C02 control programmes In Fig. 2 t h e t e m p e r a t u r e r e s p o n s e on 31 J a n u a r y 1988 is shown. F o u r diff e r e n t t e m p e r a t u r e s e t p o i n t s for h e a t i n g were p r o g r a m m e d o v e r t h e 24-h period. In t h i s e x a m p l e t h e s e t p o i n t m o d i f i c a t i o n s were stepwise, to d e m o n s t r a t e t h e s y s t e m p e r f o r m a n c e . N o r m a l l y , s e t p o i n t m o d i f i c a t i o n s t a k e place gradually w i t h 0.5 to 1.0°C p e r hour. F r o m s u n r i s e until sunset, t h e s e t p o i n t was increased p r o p o r t i o n a l l y b y 0.01 ° C p e r W m -2 at outside r a d i a t i o n levels higher
oU 25
i
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i9 t7 undershoot 15
0
4
8
i2
i6
20
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time
Fig. 2. Glasshouseair temperature response using a dog-leadPI algorithm on 31 January 1988. 5OO:
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0 "0 lU
L
200
0 0
4
8
t2
i6
20 24 time
Fig. 3. Outside global radiation on 31 January 1988. than 100 W m -2. The maximum setpoint for heating was 23 °C. These control settings resulted in the varying setpoint between 12 and 16 h as a result of the varying radiation conditions (Fig. 3). The dog-lead algorithm for the heating system reduces sag and undershoot effectively (Fig. 2 ). The dog-lead algorithm is an anti-windup modified PI controller. The setpoint value for pipe temperature is prevented from diverging from the actual value (Udink ten Cate, 1983). In this example (Fig. 4) the maximum difference between setpoint and actual value was set at 5°C. To demonstrate the effect of this algorithm thoroughly, during the morning hours the boiler temperature was maximized at 80 ° C. Thus the temperature of the heating system was limited and the setpoint for the pipe temperature was 5 ° C (dog-lead) above the actual value (Fig. 4). Despite the relatively high ambient temperature (Fig. 5), this limitation of the heating capacity resulted in a slow air-temperature response, as presented in Fig. 2. The performance of the CO2 controller is demonstrated in Fig. 6. After sunrise, an overshoot of 80 ppm occurred which lasted until the radiation level increased (Fig. 3), and CO2 was taken up by the plants. For the rest of the day
iO
dog-lead (5°C)
_ t@~@Pmt~@
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6 ~O
~5o:
7
5
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5 0
4
B
t2
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20 24 time h
4
B
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i6
20 24 time h
Fig. 4. Response of pipe temperature using a dog-lead algorithm with a maximum differer,ce between setpoint and actual value of 5 °C. Fig. 5. Windspeed and ambient temperature on 31 January 1988. 90
9OO n
c
800
F~ .RLLk
80
S ~mo E @ tJ
c
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70
600 ID
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Fig. 6. CO., response on 31 January 1988. fluctuations were within 40 ppm around the setpoint of 800 ppm, although outside radiation (Fig. 3) and windspeed (Fig. 5) fluctuated (and, consequently, CO2 uptake by the plants, and also ventilation losses). In Fig. 6 also, the response of relative humidity is added to give a complete overview of the main glasshouse environmental factors during this experiment. Humidity was not included in the control procedure.
Special control programmes Beside the standard control programmes, special algorithms and procedures for experimental research are used: - Economic optimization of CO2 enrichment by continuously maximizing the difference between the rate of production and the rate of COz consumption, both expressed in terms of economic value. This on-line optimization of the
-
-
-
C02 setpoint is based on a growth-and-production model (Nederhoff and Schapendonk, 1985) combined with a ventilation-rate model (Bot, 1983). Control of vapour transport from the glasshouse by ventilation and condensation (and thereby the level of transpiration) at a minimum level, based on a simple vapour-balance model (Bakker, 1986). Minimum pipe temperature and windowsetting depending on the humidity in the glasshouse. CO2 control by a disturbance variable feed-forward/feedback control algorithm based on a photosynthesis and ventilation-rate model (Bakker, 1985). Control of an aluminium slat screen. Pad and fan cooling.
Data handling and statistical analysis All recorded data are compiled in a direct-access file. Tables and graphs can be made by an interactive programme from momentary or average values over the previous 4 days. A selection of required data records from the database is compiled by a SORT programme and transferred automatically to the level 2 system every day. Minute-interval readings are used if new algorithms or fastresponding physical processes are studied. Most researchers however, use 15-minute or hourly averages for statistical analysis and data storage. Several software packages are available (GENSTAT, GLIM ). The environmental data are used for the development of physical models, for simulation studies, or, in combination with manually recorded plant data, for the development of dynamic plant-growth and production models. FUTURE RESEARCH In 1988 a new glasshouse block will be connected to the system for research on evapotranspiration of glasshouse crops. Data will be collected from nine balances while irrigation frequency, drainage and EC will also be monitored and controlled. In cooperation with the Agricultural University and Institutes in Wageningen, a research project is set up to develop control procedures in which physical and physiological models are used to optimize growth and production. Optimum conditions in the root environment also have to be assessed, as well as interactions between glasshouse and root environment (Bakker and Sonneveld, 1988).
CONCLUSIONS T h e d i s t r i b u t e d s y s t e m is a p o w e r f u l a n d flexible s y s t e m o f w h i c h h a r d - a n d s o f t w a r e c a n e a s i l y be m o d i f i e d t o c o p e w i t h f u t u r e d e v e l o p m e n t s in r e s e a r c h on glasshouse climate control and plant responses. D u e t o t h e flexibility o f t h e t o t a l s y s t e m , n e w m i c r o s c o n t r o l l i n g t h e r o o t e n v i r o n m e n t c a n easily be c o n n e c t e d . T h e r e b y i n t e r d e p e n d e n t c o n t r o l o f g l a s s h o u s e a n d r o o t e n v i r o n m e n t c a n be s t u d i e d .
REFERENCES Bakker, J.C., 1985. A C02 algorithm based on simulated photosynthesis and ventilation rate. Acta Hortic., 174: 387-392. Bakker, J.C., 1986. Measurement of canopy transpiration or evapotranspiration by means of a simple vapour balance model. Agric. For. Meteorol., 37:133-141. Bakker, J.C. and Sonneveld, C., 1988. Calcium deficiency of glasshouse cucumber as affected by environmental humidity and mineral nutrition. J. Hortic. Sci., 63: 241-246. Bot, G.P.A., 1983. Greenhouse climate: from physical processes to a dynamic model. Ph.D. dissertation, Agricultural University, Wageningen, 240 pp. Challa, H., Bakker, J.C., Bot, G.P.A., Udink ten Cate, A.J. and Van de Vooren, J., 1980. Economic optimization of energy consumption in an early cucumber crop. Acta Hortic., 118:191-199. De Koning, A., 1988. An algorithm for controlling the average 24-hour temperature in glasshouses. J. Hortic. Sci., 63: 105-109. Nederhoff, E.M. and Schapendonk, A.H.M.C., 1985. Effects of environmental conditions on growth and production of cucumber; comparison between empirical and simulation data. Acta Hortic., 174: 251-258. Stanghellini, C., 1987. Transpiration of greenhouse crops, an aid to climate management. Ph.D. dissertation, Agricultural University, Wageningen, 150 pp. Tantau, H.J., 1985. Greenhouse climate control using mathematical models. Acta Hortic., 174: 449-459. Udink ten Cate, A.J., 1983. Modelling and {adaptive) control of greenhouse climates. Ph.D. dissertation, Agricultural University, Wageningen, 159 pp. Van de Vooren, J., 1975. A computer for crop research and climate control in glasshouses. Acta Hortic., 51: 169-174. Van de Vooren, J. and Strijbosch, Th., 1979. Glasshouse ventilation control. Acta Hortic., 106: 117-123. Van Keulen, J. and Oostindjer, J., 1986. Ethernet network maintenance. Rep. TFDL, Technical Physical Service, Wageningen, 39 pp.
1
A distributed System for Glasshouse Climate Control, Data Acquisition and Analysis J.C. BAKKER, L. VAN DEN BOS, A.J. ARENDZEN and L. SPAANS
Glasshouse Crops Research Station (GCRS), P.O. Box 8, 2670 AA Naaldwijk (The Netherlands) (Accepted 17 February 1988)
ABSTRACT Bakker, J.C., Van den Bos, L., Arendzen, A.J. and Spaans, J., 1988. A distributed system for glasshouse climate control, data acquisition and analysis. Comput. Electron. Agric., 3: 1-9. To cope with future developments in glasshouse climate control, a distributed computer system is installed at the GCRS. The hard- and software of the system are described. The system has four types of computers networked together by Ethernet. It controls and collects data from eight glasshouse blocks with over 70 different compartments. The advantages of this system are: reliability, speed, flexibility, easy servicing, user-friendliness and easy expansibility.
I NTRODUCTION
In 1974 a Siemens 330 process computer was installed at the GCRS in Naaldwijk to control the climate in a 24-compartment glasshouse (Van de Vooren, 1975 ). Since then the number of computer-controlled glasshouse compartments has gradually increased. After 13 years of successful use the Siemens 330 system has been replaced by a new distributed system to cope with future developments in glasshouse climate control. The knowledge about physical processes (Bot, 1983; Stanghellini, 1987) and control processes in the glasshouse (Udink ten Care, 1983; Tantau, 1985), together with plant-growth models (Nederhoff and Schapendonk, 1985) will form the basis for new environmental control procedures. Within the next 10 years new control procedures, based on economic optimization of production (Challa et al., 1980), are expected. The climate-control system needs, therefore, besides simple control procedures (comparable to those available to growers), the possibility of using large simulation-based optimization control procedures. Furthermore, interdependent control of glasshouse and root environment is expected in the near future. To cope with these requirements the system should be reliable, fast, flexible, easily expansible, user-friendly, and have a large memory capacity. In this report the hard- and software of the new system are described, to0168-1699/88/$03.50
© 1988 Elsevier Science Publishers B.V.
gether with recent developments in glasshouse climate control and future research at the GCRS. SYSTEM COMPONENTS AND DATA ACQUISITION
The system is set up with three levels of computer systems linked by a local area network (Ethernet, IEEE 802.3) (Fig. 1). Ethernet is an IEEE standard developed in cooperation between Xerox, Intel and Digital. The signals are Manchester-encoded digital signals, the communication protocol is based on the CSMA/CD technique, and the transport speed is 10 Mbits s- 1. A detailed description of Ethernet is given by Van Keulen and Oostindjer (1986). The lowest-level micro (level 0), situated near the glasshouse, measures physical data: temperature, humidity, C02 and light, and controls pipe temperatures, ventilation windows, thermal screens, CO2 dosing valves and supplementary lighting. Each micro controls up to three different pipe-heating systems, wind- and leeward (roof) ventilation, two thermal screens, a COz valve (pure CO2 or from natural-gas combustion) and supplementary lighting in three to ten different glasshouse compartments, depending on the required I/O. One level-0 micro is used for measurement of outside weather conditions (temperature, direct and diffuse radiation, PAR, windspeed and direction, humidity, rainfall, sunshine and COe). Details of the different sensors are listed in Table 1.
~ - -
LAN (ETHERNET)
Fig. 1. Outline of the distributed system for glasshouse climate control and data acquisition: DA, data acquisition system; DELNI, local area network interconnect; LAN, local are network; TS, terminal server (DEC server 100 or 200).
TABLE1 Sensors~rclimatemeasurementsinsideandoutsidetheglasshouses Temperature
Humidity
Temperature/Humidity (outside) CO~ Radiation: Global Diffuse PAR
Net Sunshine Windspeed/direction Rainfall
4-wire RTD (Pt-100) DIN 43760 copper-constantan thermocouples (only in combination with KAYE or Acurex data acquisition systems ) aspirated dry-wet bulb psychrometers with RTD (made by the Technical Physical Service for Agriculture, TFDL, in Wageningen ) THIES Clima MZTI 7Z50, + 2~ Siemens IRGA ZFDSC, 0-3000 ppm, +_1% Siemens IRGA Ultramat P22, 0-5000 ppm, + lC'i Kipp & Zonen Solarimeter C M l l . 305-2800 nm Kipp & Zonen Solarimeter CMll/121, both _+3% TFDL light sensor 21903.4,400 700 nm, _+5% BWD Industries LTD, Net Pyrradiometer CN1, ~_3~ HAENNI Solar 110 THIES Clima 43296.0.3-40 in s t 0 360= on/off: Wilhelm Lambrecht KGHP 1515 THIES Clima 540310, max 2 mm h - '. +_3%
At the GCRS, two types of computers are used at level 0, a Siemens Siematic $5-210B system and an INCAA system. The Siemens $5-210B has an 8-bit 3M H z SAB 8085 processor, 5 Kbytes of RAM, and 20 Kbytes E P R O M . It measures up to 256 input channels. The INCAA system has an 8-bit Motorola 6800 processor, 2 Kbytes of RAM, 4 Kbytes E P R O M and measures up to 128 input channels. Both systems measure RTDs (4-wire Pt-100) and mV (0-100 mV) signals with a sample time of 20 s. Each level 0 micro is connected to the LAN by a RS-232C interface, a terminal server (DEC-server 100, DSRVA-AB) and a D E L N I (Local Network Interconnect ). The level 1 system is a MicroVAX II 630 QB system with a 32-bit processor. It has 4 Mbytes of R A M and 144 Mbytes of hard-disk storage. On this computer, the control programmes ( F O R T R A N 77) are running with a cycle time of 1 min. The environmental data and calculated setpoints are stored every minute in a direct-access file for a maximum of 4 days. The level 2 is a VAX-750 superminicomputer with a 32-bit processor and 5 Mbytes of RAM, 460 Mbytes of hard disk storage and a TU-80 tape unit. All data collected at level 1 can be transferred to level 2 for statistical analysis and long-term storage. This system is also used, in an interactive programming mode, to develop growth and production models of glasshouse crops. The level 1 and 2 micros are connected to the LAN by a DELNI. For intensive measurements in glasshouse compartments, data acquisition
systems are used (KAYE dig;strip III and Acurex Autocalc). These systems can measure RTDs, mV and high-voltage signals, different types of thermocouples, and digital inputs. Both systems can be connected to the LAN by a patch-panel and a terminal server (Fig. 1), or operate stand-alone and store the data on cassette tape (Cristie CS 7, cassette terminal). For presentation of environmental data, results of statistical analysis and simulation studies, four tally matrix dot printers and an HP 7550 graphics plotter are available. Since all computers are networked together, researchers can check the performance of the control system and change setpoints at each of the 20 terminals connected. At this moment; eleven level 0 micros are installed, controlling eight glasshouse blocks with over 70 different compartments. About 2200 physical data and setpoints are stored every minute on the level 1 system. CONTROL SOFTWAREAND DATAHANDLING
Standard climate control programmes and alarm procedures The standard control programmes are able to control temperature (three different pipe-heating systems per compartment, and ventilation), CO2 enrichment (pure C02 or from natural-gas combustion), two thermal screens, and supplementary lighting. The heating system is controlled by the dog-lead algorithm (Udink ten Cate, 1983); ventilation and the thermal screens are proportionally controlled, CO2 by a PI controller. Setpoints for heating and ventilation and minimum settings of pipe temperature and ventilation can be influenced according to outside conditions. Thermal screens can be used for energy saving or shading and can also be influenced according to outside conditions. The routine to calculate proportions is a renewed version of the one described by Van de Vooren and Strijbosch (1979). For temperature control and thermal screens, four different setpoints can be programmed over a period of 24 h; for CO2 enrichment and root heating, two periods are available. The different periods can be related to absolute time or to sunrise and sunset. All setpoints can be used as fixed setpoints or, depending on outside or inside conditions, as presented in Table 2. For temperature control, an extra control procedure is added by which temperature can be controlled at a 24-h mean setpoint. In this procedure the setpoint for the night temperature is calculated on-line, depending on the temperature integral received and the remaining night-length (De Koning, 1988). The VAX-750 has simple control procedures which are activated automatically to take over the temperature control in all glasshouses in the event the level-1 system fails. If both levels 1 and 2 fail, the level 0 continues control at
TABLE 2 Standard control procedures Setpoints
Number of Depending on periods Outside conditions
Inside conditions
radiation wind temperature temperature humidity Heating Setpoint Minimum pipe Maximum pipe Root heating Ventilation Setpoint temperature Setpoint humidity Minimum window Maximum window Thermal screen Setpoint CO~ enrichment Supplementary lighting on/off
4 4 4 2
fixed setpoint watertemperature
4 4 4 1
+ + -
+ +
+ +
4 2 2
+ + +
+ +h -
+ _ -
+
+
+
-
+
+
m
"Setpoint corrected on line to maintain a 24-h average temperature. ~Depending on ventilation rate. the s e t p o i n t s last received. A ' w a t c h - d o g ' triggers a n a l a r m s y s t e m if level 1 or level 2 fails. F u r t h e r m o r e , e a c h level 0 c a n trigger t h e a l a r m s y s t e m in t h e e v e n t this m i c r o or t h e c o m m u n i c a t i o n fails, or if t h e g l a s s h o u s e t e m p e r a t u r e in one of the c o m p a r t m e n t s is b e y o n d t h e a l a r m limits ( t h e s e limits c a n be c h a n g e d by an interactive programme). A l a r m m e s s a g e s are p r i n t e d a n d ( d u r i n g t h e nights a n d w e e k e n d s ) a p h o necall is m a d e to w a r n t h e t e c h n i c a l service a n d o p e r a t o r . E a c h day a list of all n o n - f u n c t i o n i n g s e n s o r s is p r i n t e d .
Performance of the standard temperature and C02 control programmes In Fig. 2 t h e t e m p e r a t u r e r e s p o n s e on 31 J a n u a r y 1988 is shown. F o u r diff e r e n t t e m p e r a t u r e s e t p o i n t s for h e a t i n g were p r o g r a m m e d o v e r t h e 24-h period. In t h i s e x a m p l e t h e s e t p o i n t m o d i f i c a t i o n s were stepwise, to d e m o n s t r a t e t h e s y s t e m p e r f o r m a n c e . N o r m a l l y , s e t p o i n t m o d i f i c a t i o n s t a k e place gradually w i t h 0.5 to 1.0°C p e r hour. F r o m s u n r i s e until sunset, t h e s e t p o i n t was increased p r o p o r t i o n a l l y b y 0.01 ° C p e r W m -2 at outside r a d i a t i o n levels higher
oU 25
i
2t:
i9 t7 undershoot 15
0
4
8
i2
i6
20
24
time
Fig. 2. Glasshouseair temperature response using a dog-leadPI algorithm on 31 January 1988. 5OO:
4OO: .
0 "0 lU
L
200
0 0
4
8
t2
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Fig. 3. Outside global radiation on 31 January 1988. than 100 W m -2. The maximum setpoint for heating was 23 °C. These control settings resulted in the varying setpoint between 12 and 16 h as a result of the varying radiation conditions (Fig. 3). The dog-lead algorithm for the heating system reduces sag and undershoot effectively (Fig. 2 ). The dog-lead algorithm is an anti-windup modified PI controller. The setpoint value for pipe temperature is prevented from diverging from the actual value (Udink ten Cate, 1983). In this example (Fig. 4) the maximum difference between setpoint and actual value was set at 5°C. To demonstrate the effect of this algorithm thoroughly, during the morning hours the boiler temperature was maximized at 80 ° C. Thus the temperature of the heating system was limited and the setpoint for the pipe temperature was 5 ° C (dog-lead) above the actual value (Fig. 4). Despite the relatively high ambient temperature (Fig. 5), this limitation of the heating capacity resulted in a slow air-temperature response, as presented in Fig. 2. The performance of the CO2 controller is demonstrated in Fig. 6. After sunrise, an overshoot of 80 ppm occurred which lasted until the radiation level increased (Fig. 3), and CO2 was taken up by the plants. For the rest of the day
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Special control programmes Beside the standard control programmes, special algorithms and procedures for experimental research are used: - Economic optimization of CO2 enrichment by continuously maximizing the difference between the rate of production and the rate of COz consumption, both expressed in terms of economic value. This on-line optimization of the
-
-
-
C02 setpoint is based on a growth-and-production model (Nederhoff and Schapendonk, 1985) combined with a ventilation-rate model (Bot, 1983). Control of vapour transport from the glasshouse by ventilation and condensation (and thereby the level of transpiration) at a minimum level, based on a simple vapour-balance model (Bakker, 1986). Minimum pipe temperature and windowsetting depending on the humidity in the glasshouse. CO2 control by a disturbance variable feed-forward/feedback control algorithm based on a photosynthesis and ventilation-rate model (Bakker, 1985). Control of an aluminium slat screen. Pad and fan cooling.
Data handling and statistical analysis All recorded data are compiled in a direct-access file. Tables and graphs can be made by an interactive programme from momentary or average values over the previous 4 days. A selection of required data records from the database is compiled by a SORT programme and transferred automatically to the level 2 system every day. Minute-interval readings are used if new algorithms or fastresponding physical processes are studied. Most researchers however, use 15-minute or hourly averages for statistical analysis and data storage. Several software packages are available (GENSTAT, GLIM ). The environmental data are used for the development of physical models, for simulation studies, or, in combination with manually recorded plant data, for the development of dynamic plant-growth and production models. FUTURE RESEARCH In 1988 a new glasshouse block will be connected to the system for research on evapotranspiration of glasshouse crops. Data will be collected from nine balances while irrigation frequency, drainage and EC will also be monitored and controlled. In cooperation with the Agricultural University and Institutes in Wageningen, a research project is set up to develop control procedures in which physical and physiological models are used to optimize growth and production. Optimum conditions in the root environment also have to be assessed, as well as interactions between glasshouse and root environment (Bakker and Sonneveld, 1988).
CONCLUSIONS T h e d i s t r i b u t e d s y s t e m is a p o w e r f u l a n d flexible s y s t e m o f w h i c h h a r d - a n d s o f t w a r e c a n e a s i l y be m o d i f i e d t o c o p e w i t h f u t u r e d e v e l o p m e n t s in r e s e a r c h on glasshouse climate control and plant responses. D u e t o t h e flexibility o f t h e t o t a l s y s t e m , n e w m i c r o s c o n t r o l l i n g t h e r o o t e n v i r o n m e n t c a n easily be c o n n e c t e d . T h e r e b y i n t e r d e p e n d e n t c o n t r o l o f g l a s s h o u s e a n d r o o t e n v i r o n m e n t c a n be s t u d i e d .
REFERENCES Bakker, J.C., 1985. A C02 algorithm based on simulated photosynthesis and ventilation rate. Acta Hortic., 174: 387-392. Bakker, J.C., 1986. Measurement of canopy transpiration or evapotranspiration by means of a simple vapour balance model. Agric. For. Meteorol., 37:133-141. Bakker, J.C. and Sonneveld, C., 1988. Calcium deficiency of glasshouse cucumber as affected by environmental humidity and mineral nutrition. J. Hortic. Sci., 63: 241-246. Bot, G.P.A., 1983. Greenhouse climate: from physical processes to a dynamic model. Ph.D. dissertation, Agricultural University, Wageningen, 240 pp. Challa, H., Bakker, J.C., Bot, G.P.A., Udink ten Cate, A.J. and Van de Vooren, J., 1980. Economic optimization of energy consumption in an early cucumber crop. Acta Hortic., 118:191-199. De Koning, A., 1988. An algorithm for controlling the average 24-hour temperature in glasshouses. J. Hortic. Sci., 63: 105-109. Nederhoff, E.M. and Schapendonk, A.H.M.C., 1985. Effects of environmental conditions on growth and production of cucumber; comparison between empirical and simulation data. Acta Hortic., 174: 251-258. Stanghellini, C., 1987. Transpiration of greenhouse crops, an aid to climate management. Ph.D. dissertation, Agricultural University, Wageningen, 150 pp. Tantau, H.J., 1985. Greenhouse climate control using mathematical models. Acta Hortic., 174: 449-459. Udink ten Cate, A.J., 1983. Modelling and {adaptive) control of greenhouse climates. Ph.D. dissertation, Agricultural University, Wageningen, 159 pp. Van de Vooren, J., 1975. A computer for crop research and climate control in glasshouses. Acta Hortic., 51: 169-174. Van de Vooren, J. and Strijbosch, Th., 1979. Glasshouse ventilation control. Acta Hortic., 106: 117-123. Van Keulen, J. and Oostindjer, J., 1986. Ethernet network maintenance. Rep. TFDL, Technical Physical Service, Wageningen, 39 pp.