Temperature control in a MISO greenhouse by inverting its fuzzy model

Márquez-Vera, Marco Antonio; Ramos-Fernández, Julio C.; Cerecero‐Natale, Luis F.; Lafont, Frédéric; Balmat, Jean-François; Esparza-Villanueva, Jorge I.

doi:10.1016/j.compag.2016.04.005

Cited by 59 publications

(14 citation statements)

References 18 publications

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“…On the other hand, the results obtained in [8] highlight the improvements that can be achieved in terms of greenhouse temperature control when a fuzzy controller is used with particle swarm optimization. Finally, it should be emphasized that the application developed in this work, allowed for man-machine interaction, offering access to the configuration, monitoring, and control of a fuzzy system, as proposed in [5][6][7][8].…”

Section: Discussionmentioning

confidence: 99%

“…To meet these requirements, different intelligent control strategies such as fuzzy logic have been discussed, and achievements have been made in the remote control of climatic variables [2][3][4]. In addition, research has been conducted using different versions of fuzzy controllers such as traditional [5], inverted [6], adaptive [7], and improved via particle swarm optimization [8]. It also highlights the growing use of neural networks for smart frost control [9], the dynamic modeling of temperature and relative humidity [10], and climate control and energy saving in different types of greenhouses [11].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Low-Cost Fuzzy Logic Control for Greenhouse Environments with Web Monitoring

Robles-Algarín¹,

Cabarcas²,

Llanos³

2017

Electronics

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Abstract:The design and implementation of a low-cost system for monitoring and remote control of a greenhouse using fuzzy logic is presented. For the control system, an Arduino Mega board was programmed with a fuzzy algorithm to monitor and perform control actions for environmental temperature, soil moisture, relative humidity, and lighting. A website was designed to visualize the main indicators of agricultural interest and to get access to tools such as forced ventilation, misting systems, and sprinkler irrigation. For connectivity to the webpage, an Arduino Ethernet Shield was used. Thus, it was possible to establish a local area network and monitor and control the greenhouse climate variables manually or automatically. The application designed allowed access to the configuration, monitoring, and control of climatic conditions in the greenhouse. The effectiveness of fuzzy logic to control nonlinear systems was therefore verified without the mathematical model of the plant. Thus, the use of resources for a gable roof greenhouse prototype was optimized.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Low-Cost Fuzzy Logic Control for Greenhouse Environments with Web Monitoring

Robles-Algarín¹,

Cabarcas²,

Llanos³

2017

Electronics

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“…For example, fuzzy systems have achieved significant results in the area of precision irrigation [135] and microclimate control. Several techniques and approaches have been presented, including inverting fuzzy model [136] , reconfigurable adaptive fuzzy fault-hiding control [137] , TakagiSugeno fuzzy modeling [138] , conventional fuzzy logic control for smart greenhouses [102] , and decentralized decoupling fuzzy logic controller [139] . These solutions have shown a more effective set-point tracking compared with the conventional PID controllers.…”

Section: Advances In Microclimate Controlmentioning

confidence: 99%

Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture

Shamshiri

Kalantari

Ting

et al. 2018

International Journal of Agricultural and Biological Engineering

273

185

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Greenhouse cultivation has evolved from simple covered rows of open-fields crops to highly sophisticated controlled environment agriculture (CEA) facilities that projected the image of plant factories for urban agriculture. The advances and improvements in CEA have promoted the scientific solutions for the efficient production of plants in populated cities and multi-story buildings. Successful deployment of CEA for urban agriculture requires many components and subsystems, as well as the understanding of the external influencing factors that should be systematically considered and integrated. This review is an attempt to highlight some of the most recent advances in greenhouse technology and CEA in order to raise the awareness for technology transfer and adaptation, which is necessary for a successful transition to urban agriculture. This study reviewed several aspects of a high-tech CEA system including improvements in the frame and covering materials, environment perception and data sharing, and advanced microclimate control and energy optimization models. This research highlighted urban agriculture and its derivatives, including vertical farming, rooftop greenhouses and plant factories which are the extensions of CEA and have emerged as a response to the growing population, environmental degradation, and urbanization that are threatening food security. Finally, several opportunities and challenges have been identified in implementing the integrated CEA and vertical farming for urban agriculture.

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“…Also, several studies have established the importance and usefulness of the FLC controller and its tool to solve the problem of complexity and non-linearity of the greenhouse system [15] from which presented a comparative study of a basic fuzzy controller and optimized fuzzy controllers to show their advantages and disadvantages. The author in [16] have developed a fuzzy modeling application to control the indoor air temperature of a MISO greenhouse, [17] have used this application with a new approach that automatically organizes a fuzzy flat system into a hierarchical collaborative architecture, this architecture adapted to transfer the information contained in the fuzzy rule sets to another fuzzy subsystem.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Climate Control System inside a Greenhouse

Labidi¹,

Chouchaine²,

Mami³

2021

IJACSA

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An agricultural greenhouse is an environment to ensure intensive agricultural production. The favorable climatological conditions (temperature, lighting, humidity ...) for agricultural production must be reproduced in a non-natural way by controlling these parameters using several actuators (heating/air conditioning, ventilation, and humidifier/ dehumidifier). The objective of this study is to control the humidity inside the greenhouse; it is a problem that remains to be negotiated. To that end, an actuator based on a humidifier and a dehumidifier was installed in an experimental greenhouse and activated by a fuzzy logic controller to achieve the desired optimal indoor humidity in the greenhouse.

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Temperature control in a MISO greenhouse by inverting its fuzzy model

Cited by 59 publications

References 18 publications

Low-Cost Fuzzy Logic Control for Greenhouse Environments with Web Monitoring

Low-Cost Fuzzy Logic Control for Greenhouse Environments with Web Monitoring

Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture

Intelligent Climate Control System inside a Greenhouse

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