A model-free control strategy for an experimental greenhouse with an application to fault accommodation

Writing down mathematical models of agricultural greenhouses and regulating them via advanced controllers are challenging tasks since strong perturbations, like meteorological variations, have to be taken into account. This is why we are developing here a new model-free control approach and the corresponding intelligent controllers, where the need of a good model disappears. This setting, which has been introduced quite recently and is easy to implement, is already successful in many engineering domains. Tests on a concrete greenhouse and comparisons with Boolean controllers are reported. They not only demonstrate an excellent climate control, where the reference may be modified in a straightforward way, but also an efficient fault accommodation with respect to the actuators

Neural Network System Identification and Controlling of Multivariable System

Most of the industrial processes are multivariable in nature. Here Greenhouse system is considered which is the important application in agricultural process. Greenhouse is to improve the environmental conditions in which plants are grown .In this paper we have proposed identification of greenhouse system using input and output data sets to estimate the best model and validate the model. For MIMO systems, Neural Network System identification provides a better alternative to find their system transfer function. The results were analyzed and the model is obtained. From this obtained model ,the system is controlled by conventional method. By these method we can identify the model and control the complicated systems like Greenhouse

Design and Implementation of Fuzzy Controller for Non-Linear Thermally Insulated MIMO Greenhouse Building Utilizing Weather Conditions and Ground Temperature

The increased demand of electricity and water consumption for cooling and heating processes together with the continuous increase in earth temperature due to greenhouse gases emission urged the utilization of sustainable, affordable and clean energy resources. Globally, the biggest amount of water is consumed for agricultural purposes. Domestically, in Abu Dhabi Emirate, the agriculture sector consumes over 50% of the supplied water. Part of this consumption is due to the evaporative cooling approach that is typically used in cooling greenhouses. This approach utilizes a large amount of water and energy to maintain the greenhouse temperature within the desired range. Ground Heat-Exchanger is an environmentally-friendly solution used for heating or cooling applications. It is based on seasonal temperature difference between the ground and the ambient which varies with depth. As depth of ground increases, the temperature fluctuation decreases because of the soil high thermal inertia and the time lag in temperature fluctuation between the surface and the ground. The aim of this thesis is to design a control system using fuzzy logic controller to study the feasibility of utilizing weather conditions and soil temperature in cooling or heating processes of a special type of greenhouses. The proposed control system takes a decision of either utilizing the outside weather conditions or using the soil temperature. The study is conducted on a thermally insulated greenhouse system equipped with ground-to-air heat exchanger, actuated windows, fans, and sensors and the proposed controller performance is compared to a logical and conventional ON/OFF controllers. Results show the proposed control system is capable of maintaining the greenhouse temperature within the desired range for most of the day hours in winter utilizing only the weather and soil temperatures. However, when the temperature is extremely hot, especially in summer, the ground heat exchanger can be only used for pre-cooling with a capability of reducing the ambient temperature of about 6ºC on average. In such extremely hot periods, an auxiliary cooling unit has to be deployed for further cooling. In addition, results reveal that fuzzy controller consumes less power than the logical and the ON/OFF controller when operating the system actuators

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Estimating the global temperature change by means of a fuzzy logic model obtained from a simple climate model

Ponencia presentada en: VI Congreso Internacional de la Asociación Española de Climatología celebrado en Tarragona del 8 al 11 de octubre de 2008.[EN]In this work a simple box model of the ocean-atmosphere system is used to asses the response of the simulated global mean temperature to expected changes in the surface thermal forcing at the year 2000, as well as to variations of two key parameters, namely ocean thermal diffusivity and the atmospheric feedback. Such experiments provide the input data needed to build fuzzy logic models that are able to deal with the uncertainties associated to the model parameters. Two fuzzy logic approaches are presented in this article.[ES]En este trabajo se utiliza un modelo de cajas del sistema océano-atmósfera para estudiar la respuesta de la temperatura promedio global a cambios en el forzamiento radiativo y a la variación de dos parámetros importantes del modelo: la difusividad térmica del océano y la sensitividad de la atmósfera (procesos de retroalimentación). A partir de los campos de temperatura obtenidos, se construyen dos modelos basados en lógica difusa

Deployment and control of adaptive building facades for energy generation, thermal insulation, ventilation and daylighting: A review

A major objective in the design and operation of buildings is to maintain occupant comfort without incurring significant energy use. Particularly in narrower-plan buildings, the thermophysical properties and behaviour of their façades are often an important determinant of internal conditions. Building facades have been, and are being, developed to adapt their heat and mass transfer characteristics to changes in weather conditions, number of occupants and occupant’s requirements and preferences. Both the wall and window elements of a facade can be engineered to (i) harness solar energy for photovoltaic electricity generation, heating, inducing ventilation and daylighting (ii) provide varying levels of thermal insulation and (iii) store energy. As an adaptive façade may need to provide each attribute to differing extents at particular times, achieving their optimal performance requires effective control. This paper reviews key aspects of current and emerging adaptive façade technologies. These include (i) mechanisms and technologies used to regulate heat and mass transfer flows, daylight, electricity and heat generation (ii) effectiveness and responsiveness of adaptive façades, (iii) appropriate control algorithms for adaptive facades and (iv) sensor information required for façade adaptations to maintain desired occupants’ comfort levels while minimising the energy use

A fuzzy micro-climate controller for small indoor aeroponics systems

The Indonesian agricultural sector faces challenges producing affordably priced food using sustainable practices. A soilless cultural practice, such as indoor aeroponics, is a compelling alternative to conventional agriculture. The objective of the present study was to develop a system for micro-climate management in a pilot-scale indoor aeroponics system. For this purpose, three fuzzy logic controllers were developed and evaluated to maintain plant chamber parameters (temperature, relative humidity, and light intensity) at desired set points controlled by embedded system controls designed using BASCOM-AVR software. The results showed that the fuzzy controllers provided excellent responses and experienced relatively low errors in all controlled parameters. All parameters changes followed the set point very smoothly and responded accordingly.The averaged percent of working times in which temperature, relative humidity, and light intensity were maintained within less than ±1°C, ±5%, and ±30 lux from the set points were found to be 88.43%, 95.91%, and 85.51%, respectively