Automation of microclimate in greenhouses

An agricultural greenhouse is a complex system with many input features. Taking these features into consideration creates favorable conditions for the production of plants. The parameters are temperature and internal humidity, which have a significant impact on the yield. The aim of this study was to propose a dynamic simulation model in the MATLAB/Simulink environment for experimental validation. In addition, a fuzzy controller for the indoor climate of the greenhouse with an asynchronous motor for ventilation, heating, humidification, etc. has been designed. The model includes an intelligent control system for these drives in order to ensure optimal indoor climate. The dynamic model was validated by comparing simulation results with experimental measurement data. These results showed the effectiveness of the control strategy in regulating the greenhouse indoor climate.

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AUTOMATION OF MICROCLIMATE WITH THE USE OF MODERN EQUIPMENT IN GREENHOUSES AND GREENHOUSES

OF THE VIII INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE «INNOVATIVE TECHNOLOGIES IN SCIENCE AND EDUCATION» («ITSE 2020» CONFERENCE) ◽

10.23947/itno.2020.237-242 ◽

2020 ◽

Author(s):

M.A. Ganzhur ◽

◽

A.P Ganzhur ◽

D.L. Romanov

Keyword(s):

Intelligent Control ◽

Experimental Validation ◽

Fuzzy Controller ◽

Asynchronous Motor ◽

Plant Production ◽

Indoor Climate ◽

Intelligent Control System ◽

Dynamic Simulation Model ◽

Simulation Results ◽

Favorable Conditions

An agricultural greenhouse is a complex and system with many input characteristics. Accounting for which creates favorable conditions for plant production. The parameters are temperature and internal humidity, which have a significant impact on the yield. The aim of this study was to propose a dynamic simulation model in MATLAB / Simulink for experimental validation. In addition, the fuzzy controller has been designed to control the indoor climate of the greenhouse with an asynchronous motor for ventilation, heating, humidification, etc. The model has implemented an intelligent control system for these drives to ensure an optimal indoor climate. The dynamic model was validated by comparing simulation results with experimental measurements. These results showed the effectiveness of the control strategy in regulating the indoor climate of the greenhouse.

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The Design of Neuro-Fuzzy Control System Based on Data Fusion

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.678.406 ◽

2014 ◽

Vol 678 ◽

pp. 406-409

Author(s):

Xiao Rong Fu

Keyword(s):

Nonlinear Systems ◽

Data Fusion ◽

Intelligent Control ◽

Fuzzy Controller ◽

Control Technique ◽

Fusion Method ◽

Neuro Fuzzy ◽

Simulation Results ◽

Using Data ◽

Self Learning

An adaptive neuro-fuzzy controller of nonlinear systems is presented based on data fusion method. It reduces the input dimension of the controller using data fusion technique and simplifies the fuzzy controller’s design. The fuzzy controller was designed with self-learning of neural networks. The simulation results show that the performance of the system is superior to that using conventional fuzzy controller. It is rewarding for the research on combination of data fusion method and intelligent control technique of nonlinear systems.

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Intelligent Control System of Biotechnological Objects with Fuzzy Controller and Noise Filtration Unit

2018 International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T) ◽

10.1109/infocommst.2018.8632007 ◽

2018 ◽

Cited By ~ 1

Author(s):

Alla Dudnyk ◽

Vitaliy Lysenko ◽

Natalia Zaets ◽

Dmytro Komarchuk ◽

Taras Lendiel ◽

...

Keyword(s):

Control System ◽

Intelligent Control ◽

Fuzzy Controller ◽

Intelligent Control System ◽

Filtration Unit

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Intelligent Control of the Microclimate of an Agricultural Greenhouse Powered by a Supporting PV System

Applied Sciences ◽

10.3390/app10041350 ◽

2020 ◽

Vol 10 (4) ◽

pp. 1350 ◽

Cited By ~ 3

Author(s):

Jamel Riahi ◽

Silvano Vergura ◽

Dhafer Mezghani ◽

Abdelkader Mami

Keyword(s):

Dynamic Model ◽

Agricultural Production ◽

Fuzzy Controller ◽

Intelligent System ◽

Mimo System ◽

Asynchronous Motor ◽

Indoor Climate ◽

Pv System ◽

Production Temperature ◽

Two Parameters

An agricultural greenhouse is a complex and Multi-Input Multi-Output MIMO system in which the internal parameters create a favorable microclimate for agricultural production. Temperature and internal humidity are two parameters that have a major impact on greenhouse yield. The objective of this study was to propose a simulated dynamic model in a MATLAB/Simulink environment for experimental validation. Moreover, a fuzzy controller was designed to manage a greenhouse indoor climate by means of an asynchronous motor for ventilation, heating, humidification, etc. An intelligent system to control these actuators for an optimal inside climate was implemented in the model. The dynamic model was validated by comparing the simulation results to experimental measurements. These results showed the effectiveness of the control strategy in regulating the greenhouse indoor climate. Finally, a photovoltaic generator was modeled, with the aim of reducing the costs of agricultural production. It feeds the asynchronous motor with a vector control optimized by fuzzy logic that drives a variable speed fan.

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Development of an intelligent electric drive control system anchor winch

MORSKIE INTELLEKTUAL`NYE TEHNOLOGII ◽

10.37220/mit.2021.54.4.051 ◽

2021 ◽

pp. 195-200

Author(s):

С.П. Черный ◽

А.В. Бузикаева ◽

А.К. Тимофеев

Keyword(s):

Control System ◽

Control Systems ◽

Intelligent Control ◽

Electric Drive ◽

Fuzzy Controller ◽

Electric Drives ◽

Intelligent Control System ◽

Advantages And Disadvantages ◽

Drive Control ◽

Control Procedures

Данная работа посвящена моделированию интеллектуальной системы управления электроприводом якорной лебедки с применением теории нечетких множеств. Был приведен анализ существующих систем управления электроприводами якорно-швартовных узлов основанных на различных традиционных схемах регулирования, показаны достоинства и недостатки традиционных систем управления, а также выявлены основные возмущения, носящие существенно-недетерминированный характер. Процедуры интеллектуального управления в реализуемой модели системы управления электроприводом реализуются нечетким регулятором. Интеллектуальная система управления в своей основе имеет нечеткий регулятор с алгоритмом вывода Сугено, формализация входных сигналов по ошибке осуществляется двумя лингвистическими переменными. Кроме того, показано преимущество предлагаемого подхода при построении систем управления электроприводами якорно-швартовных узлов на основании базовых показателей качества. This paper is devoted to the modeling of an intelligent control system for the electric drive of an anchor winch using the theory of fuzzy sets. The analysis of the existing control systems for electric drives of anchor and mooring units based on various traditional control schemes was given, the advantages and disadvantages of traditional control systems were shown, and the main disturbances of a significantly non-deterministic nature were identified. Intelligent control procedures in the implemented model of the electric drive control system are implemented by a fuzzy controller. The intelligent control system is based on a fuzzy controller with the Sugeno output algorithm, the formalization of input signals by error is carried out by two linguistic variables. In addition, the advantage of the proposed approach in the construction of control systems for electric drives of anchor and mooring units on the basis of basic quality indicators is shown.

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Research on Dissolved Oxygen Intelligent Control System in Waste Water Treatment

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.591-593.1461 ◽

2012 ◽

Vol 591-593 ◽

pp. 1461-1464

Author(s):

Hong Xing Sun ◽

Chuang Gao ◽

Na Li

Keyword(s):

Dissolved Oxygen ◽

Intelligent Control ◽

Pid Controller ◽

Single Neuron ◽

Fuzzy Controller ◽

Hot Spot ◽

Waste Water Treatment ◽

Control Effect ◽

Intelligent Control System ◽

Single Neuron Pid

By combining with the research hot spot of intelligent control, the oxygen fuzzy-single neuron PID compound controller is designed based on control increment. It contains the advantages of fuzzy controller and the single neuron PID controller. The problem of causing the oscillation in switching two kinds of controllers is solved. The results of the dissolved oxygen fuzzy-single neurons PID controller and fuzzy controller simulation are compared. The results show that the control effect of dissolved oxygen is more ideal. Thus the algorithm is effective and feasible.

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Intelligente Regelung für Stromspeichersysteme/Intelligent control for energy storage systems

wt Werkstattstechnik online ◽

10.37544/1436-4980-2021-03-75 ◽

2021 ◽

Vol 111 (03) ◽

pp. 167-171

Author(s):

Can Kaymakci ◽

Raoul Laribi ◽

Alexander Sauer

Keyword(s):

Intelligent Control ◽

Storage System ◽

Load Forecasting ◽

Measurement Data ◽

Third Party ◽

Mechatronic System ◽

Electricity Storage ◽

Storage Devices ◽

Intelligent Control System ◽

Forecasting Models

In zahlreichen mechatronischen Anwendungen kann der Einsatz von Stromspeichern die notwendige Anschlussleistung reduzieren und die Energieeffizienz durch die Nutzung von Bremsenergie erhöhen. Ein Stromspeichersystem in eine Fremdmaschine zu integrieren stellt eine Herausforderung bei der Inbetriebnahme von Hardware und Software dar. Eine automatische Systemidentifikation und Lastprognose anhand von Messdaten erleichtert den Regelungsentwurf für das mechatronische System. Dieser Beitrag erläutert eine Vorgehensmethodik für die Vorauswahl von geeigneten Methoden für die Modellbildung zur Lastprognose.   In numerous mechatronic applications it is possible to apply electricity storage devices for reducing the necessary installed load and increasing energy efficiency and thus to make use of the braking energy. The integration of an electricity storage system into a third-party machine is challenging with regard to the commissioning of hardware and software. An intelligent control system facilitates system identification based on measurement data and load forecasting within the mechatronic system. This article explains a procedure for pre-selecting suitable methods for load forecasting models.

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