Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 1 (June 2018) 27–31___________________________________________________________________________________________________________Design and Development of a Constant-Temperature Reservoir
for a Database-Driven Smart Cultivation System
Shin Wakitani

Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiuyama
Higahsi-hiroshima, Hiroshima 739-8527, Japan
Sneha Sharma

Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiuyama
Higahsi-hiroshima, Hiroshima 739-8527, Japan
Toru Yamamoto

Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiuyama
Higahsi-hiroshima, Hiroshima 739-8527, Japan
E-mail: wakitani@hiroshima-u.ac.jp, sharma-sneha-atul@hiroshima-u.ac.jp, yama@hiroshima-u.ac.jp
https://www.hiroshima-u.ac.jp

Abstract
Decreasing the number of people working in the agriculture sector is a serious problem in Japan. Production ofagricultural products in a plant factory is one of the solutions to the above problem. However, setting optimal
environmental conditions is difficult owing to the nonlinearity of the system. This research aims for the realizationof a smart cultivation system using a database-driven (DD) technique. In this paper, a pilot scale constant-temperaturereservoir with a nonlinearity regarding the Peltier device was developed, and its derivative equations were derived.
Moreover, a DD controller was designed for the system, and the simulations demonstrate that the proposed control
system could control the temperature to a wide desired temperature range.
Keywords: cultivation System, temperature control, database-driven control, nonlinear control.

1. Introduction

concentration. Although the environmental control
system, which is a cultivation system, must be designed
to optimize the above variables, a uniform system design
method that can deal with various kinds of plants has not
yet been established. Moreover, the controlled objects
have strong nonlinearity. Thus, it is difficult tomanipulate them using linear controllers such as fixed
PID controllers3, which are applied to more than 90% of
industrial systems. In addition, it may be difficult tomaintain ideal environmental conditions of a cultivation
system using such a controller due to the changing
environment around the factory and the deterioration of
the aging equipment. Because of the above situation, thisIn recent years, there has been a growing interest toward
and requirement of domestic and pesticide-free
production of agricultural products in Japan. However,the decrease in the agricultural workforce has not been
abated. Owing to the above situation, a plant factory1, 2that could automate the production process of various
agricultural products and would be able to safely andstably produce food products has garnered muchattention. The production schedule of a plant factory canbe controlled by manipulating its environmental
conditions such as temperature, humidity, and CO2

Copyright © 2018, the Authors. Published by Atlantis Press.
This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 1 (June 2018) 27–31___________________________________________________________________________________________________________Fig. 1. Appearance of a constant-temperature reservoir.

study considers the establishment of a smart cultivation
system based on a database-driven (DD) control systemdesign-method4 that utilizes a database including many
previous operational data. According to the method, thecontrolled parameters can be adaptively tuned tocorrespond to the nonlinearities and changes in theenvironmental conditions of the controlled object. In thisresearch, a pilot scale constant-temperature reservoir fora cultivation system is developed. In this system, a Peltierdevice, which is one of the thermoelectric conversion
devices, is implemented to control the temperature in thereservoir. In the Peltier device, by supplying current to
the device, one side exhausts the heat and the other sideabsorbs the heat that corresponds to the amount of thecurrent. Moreover, the exhaust and absorption surface ofthe heat can be switched by changing the direction of thecurrent. However, the amount of generated heat follows
the square of the amount of the current, thus a linear
controller with fixed control parameters does not
maintain a good control performance due to thenonlinearity. In this study, a DD temperature controller isdesigned and applied to the nonlinear system. Thismethod is expected to make the temperature follow awide range of temperature references compared with afixed PID controller. To verify the effectiveness of themethod, the derivative equations of the system arederived and a mathematical model is realized byMATLAB/Simulink. This study is organized as follows.
In Section 2, the pilot scale constant-temperature
reservoir and its mathematical model is explained. In
Section 3, the control results of the fixed PID and the DD
controller are shown. Finally, Section 4 summarizes theresearch findings.

Fig. 2. Schematic of a constant-temperature reservoir.
Table 1. System parameters.
Variablename

Explanation

Value

Resistance of Peltier device
Thermal conductivity of Peltier device
Peltier coefficient
Proportionality constant for T
Thermal resistance
Thermal capacity
Thermal resistance
Thermal capacity

3.85
10.0
1.00
5.00
0.83
5.00
39211
994.6

2. Constant-Temperature Reservoir Design
The appearance of the constant-temperature reservoir isshown in Fig. 1. The schematic and system parameters
are shown in Fig. 2 and Table 1, respectively. The
specific values of the system parameters are identified by
the genetic algorithm5.
2.1. Constant-Temperature Reservoir
A Peltier device is implemented on the system’s
background and temperature and humidity sensors areplaced on the inside of the wall. Moreover, full color
LEDs for growing plants are placed on the ceiling. The
Arduino is utilized as the controller, which canmanipulate the amount of current from the power supply
by changing the duty ratio of the PWM output voltage ofthe controller.

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Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 1 (June 2018) 27–31___________________________________________________________________________________________________________

2.2. Modeling.

In this section, the following couple of heat balance
relationships are derived:(1) Peltier device – Aluminum block.
(2) Aluminum block – Space of constant-temperature
reservoir.
A simulator based on these heat balance models isconstructed by using MATLAB/Simulink.

(6)

2.1.2.
Heat balance between aluminum block andSpace of constant-temperature reservoir
The derivative equation related into the time variation ofis given as follows:, (7)whereis given as follows:.

(8)

is the heat flow from the full colored LEDs.
Theis given by introducing the maximum
Thus, theheat discharge and command signals of each colored,, andandLED (red, green, and blue),, ,and0% u , ,100 % , respectively:.
(9)
The static property betweenof theandobtained simulation model is shown in Fig. 3. Thefigure shows the system’s nonlinearity.

Fig. 3. Static property of the simulation model.

3. Application of DD Control Technique2.1.1. Heat balance between Peltier device andaluminum block

The temperature of the constant-temperature reservoir must be
controlled properly to produce a variety of plants. In this work,
the DD control technique is applied to control the temperature.
In the DD controller design scheme, an initial database isrequired. Thus, to generate an initial database, a fixed PID
controller is applied to the system and its operation data isstored into a database.

The derivative equation regarding the time variation ofis given as follows:,(1)

where the maximum voltage of the power supply
is set to 15 V, and the range of the manipulated value
is set to 100%100%. The current in
the Peltier device can be given as follows:.

3.1. Control result by Fixed PID controller
The initial PID parameters are obtained based on model
munching. First, it is assumed that the controlled object
can be approximated as the following first-order systemwith a time delay around an equilibrium point:(2)

The, which is generated by the above current in
the Peltier device is described as follows:.

t , (3)(9)

Where, , , and are the time constant, system gain,and time delay, respectively. Using the least squares
20 aremethod, the system parameters aroundobtained as
934,0.282, and60 ,respectively. The following approximated model can beobtained by applying a first-order approximation to thetime delay:.
(4)
The exhaust heat surface of the Peltier device touches awater-cooling surface and it is assumed that thetemperature of the contact surface is given by thefollowing equation:.
(5)
Theis given as follows:

≅29.

(10)

Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 1 (June 2018) 27–31___________________________________________________________________________________________________________The control result by the fixed I-PD controller is shownin Fig. 4. In this simulation, the rise time is set to σ
500, and the discrete I-PD controller sampling time
10 is applied. Moreover, the reference temperature isgiven as follows:
03,600
20
3,600
7,200
35.
(16)
7,200
10,80025
15 10,800
14,400From Fig. 4, the controller output around35
oscillates due to the nonlinearity of the system and thetracking property is deteriorating.
Fig. 4. Control results obtained by the fixed PIDcontroller.

Fig. 6. Trajectories of PID gains corresponding to Fig. 5.

3.2. Control result by DD-PID controller

Fig. 5. Control results obtained by the DD-PID controller.

The control results in Fig. 4 and PID gains are stored into
a database, and a DD controller is designed according to
the work of Yamamoto et al.4. The control results using
the DD controller are shown in Fig. 5, and the trajectoriesof the PID gains are shown in Fig. 6. In this simulation,
the rise time is set to σ
210 s, which is faster than thefixed I-PD controller design. The results demonstrate that
good control performance is obtained by adaptively
tuning the PID gains based on the DD control technique.

Furthermore, the following I-PD control law isintroduced:
,

(11)

,
(12)
whereandare the controller and system
outputs, respectively. In this simulation,_. r is the reference temperature.
andThe following transfer function is introduced as areference model:.

4. Conclusions(13)

In this study, a constant-temperature reservoir wasdeveloped to establish a smart cultivation system basedon the DD technique. The mathematical model based on
the principal of heat balance was derived and a simulator
was constructed using MATLAB/Simulink. The DD
controller was also designed and its effectiveness wasverified using the simulation model. In a future study, thecontrol system will be implemented to the real systemand the structure of a smart cultivation system will be

σ is the required rise time of the closed loop system,
which is arbitrarily set by the user. The following
relationship can be obtained by comparing the transfer
function of the closed loop system, constructed by (10)and (11), and the reference model (13):，(14)，,,(15)30

Journal of Robotics, Networking and Artificial Life, Vol. 5, No. 1 (June 2018) 27–31___________________________________________________________________________________________________________

designed. The stability analysis of the closed-loop system
will also be considered as a future study.
References
1. T. Morimoto, T. Torii, and Y. Hashimoto, Optimal controlof physiological processes of plants in a green plantfactory, Control Engineering Practice, 3 (4) (1995) pp.
505-511.
2. T. Kozai, Plant factory in Japan-current situation andperspectives, Chron. Hortic, 53 (2) (2013), pp. 8-11
3. A. Visioli, Practical PID Control, Springer (2006)
4. T. Yamamoto, K. Takao, and T. Yamada, Design of a
Data-Driven PID Controller, IEEE Trans. Control Systems
Technology, 17 (1) (2009) pp. 29-39.
5. M. Mitchell, An introduction to genetic algorithms, MITpress (1998)

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