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Article
IoT Based Intelligent Greenhouse Monitoring and Control System

Authors: Zaidon Faisal Shenan زيدون فيصل شنان --- Ali Fadhil Marhoon علي فاضل مرهون --- Abbas A. Jasim عباس عبدالامير جاسم
Journal: Basrah Journal for Engineering Science مجلة البصرة للعلوم الهندسية ISSN: Print: 18146120; Online: 23118385 Year: 2017 Volume: 17 Issue: 1 Pages: 61-69
Publisher: Basrah University جامعة البصرة

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Abstract

Recently, the Internet of Thing technology has been usedto develop numerous applications, this paper compromisingdesign and implementation of greenhouse prototype thatintegrated with the IoT to adjust the system’s parameters andmonitor the system status from any place in this world.This system involves three intelligent controllers that designedto stabilize the temperature degree, the water level in the soil, andlight intensity inside the greenhouse prototype structure. Thesesystems have been built by two important parts: the hardwareand software.The hardware part could be achieved by designing andimplementing the control circuits, actuators, and install thesensors as well as the devices. The second one is the softwarethe part which is involves implementing Fuzzy Inference Enginethat represent the system’s brain that monitor and manage theentire process in the system to ensure the best performance.This system has been built to contain three control systems thatmeans there are three different Fuzzy controllers. In order tokeep the system practicality, the fuzzy controllers should beaggregated in single code that resides in single microcontrollerchip with additional codes that perform the IoT duties.The proposed IoT system provides the ability for specificpeople to monitor and manage their systems remotely, using aweb application with cloud technology.The major contributions of the proposed system are started bydownloading the controller’s set-points (the desiredenvironmental conditions) from the web page, transfer the setpoints to the controllers, and upload data that read fromsensors to the same web page.)


Article
Comparison Robustness of Automatic Voltage Regulator for Synchronous Generator using Neural Network and Neuro - Fuzzy controllers †

Authors: Yasir Thaier Haider2 --- Dr. Abdulrahim Thiab Humod1
Journal: IRAQI JOURNAL OF COMPUTERS,COMMUNICATION AND CONTROL & SYSTEMS ENGINEERING المجلة العراقية لهندسة الحاسبات والاتصالات والسيطرة والنظم ISSN: 18119212 Year: 2015 Volume: 15 Issue: 2 Pages: 1-10
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

Abstract – Artificial Neural Networks (ANN) and Neuro - Fuzzy controllers can be used as intelligent controllers to control non-li¬near dynamic systems through learning, which can easily accommodate the non-linearity’s, time dependencies, model uncertainty and external disturbances. Modern power systems are complex and non-linear and their operating conditions can vary over a wide range. The Nonlinear Auto-Regressive Moving Average (NARMA-L2) model system is proposed as an effective neural networks controller model to achieve the desired robust Automatic Voltage Regulator (AVR) for Synchronous Generator (SG) to maintain constant terminal voltage. The essential part of Neuro-Fuzzy comes from a common framework called adaptive networks, which unifies both neural networks and fuzzy models. The fuzzy models under the framework of adaptive networks are called Adaptive-Network-based Fuzzy Inference System (ANFIS), which possess certain advantages over neural networks. The concerned neural networks and Neuro - Fuzzy controllers for AVR is examined on different models of SG and loads. The results show that the Neuro-controllers and Neuro - Fuzzy controllers have excellent responses for all SG models and loads in view point of transient response and system stability. Also it shows that the margins of robustness for Neuro - Fuzzy controller are greater than Neuro-controller.

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