Abstract
Soil water content has a direct influence on the cooling and growth mechanisms of the plants. Crop evapotranspiration is majoring influenced by solar radiation and the air temperature, humidity and movement. An efficient irrigation system must supply and maintain, at soil root zone of the plants, the adequate amount of water that best regulate the physiological mechanisms of the plant. For this purpose, an intelligent real-time greenhouse irrigation system was implemented which uses accurate sensors for measuring soil moisture, as well to determinate the crop evapotranspiration. To avoid loss of control, it was provided fault-detection capabilities to the soil moisture sensor and used a knowledge-based approach to estimate replacement values for the faulty sensors. A model-based controller was implemented to regulate the water content at the root zone of the plants. These tasks are very complex and difficult to meet, unless microcontroller and microprocessor systems are employed, such as in the integrated management irrigation system. The system comprises four modules: Sensor/Actuation, Acquisition and Data Validation, Data Correction, Model Based Controller, and Control Signals Generation. All the modules are linked and supervised by a higher-level supervision module to achieve an intelligent irrigation.

Abstract
In this paper it will be presented the aims and some of the results obtained in the project entitled "Development of Solutions for Instrumentation, Control and Management Applied to Agricultural and Fish Production Using Renewable Energies", sponsored by the Agriculture Ministry of Portugal. The experimental set-up is composed of three demonstration greenhouses and six aquaculture tanks for production of green beans, tomatoes and tilapias. Several actuators and sensors are connected to an acquisition and control network developed at the Engineering Department of the University of Tras-os-Montes and Alto Douro, Vila Real. The environmental factors controlled are: greenhouse inside air temperature and humidity, CO(2) concentration, and soil moisture. Dissolved O(2), pH, temperature and water nitrate concentration are also controlled in the fish tanks. Three types of heating systems are being used on the greenhouses and aquaculture tanks: a geothermal water source, a solar heat pump and a wood-gas combined heater. At the end of this project it is expected to achieve an efficient control in order to maximize the ratio production/costs. This implies the use of a supervisory module to perform high level management decisions. At this level, a decision support system helps the producer to establish the chemical treatment plans. This will also help to reduce environmental contamination as well production costs.

Abstract
A fuzzy identification model and fuzzy logic controller was developed aiming the environmental control of an agriculture greenhouse. The fuzzy identification of the process was performed by the analysis of the data collected either during normal operation, as well in reaction to random generated actuating signals on the heating, ventilation and CO2 injection systems. A comparative study has been realized between fuzzy and physical models. Using the fuzzy model it was possible to implement an accurate Generalized Predictive Control (GPC) strategy in order to regulate the environment and to minimize energy consumption. The optimal setpoints were computed by means of balancing the benefits associated with the marketable produce against the costs associated with its production. The calculations use growth, photosynthesis and climate models. This work describes the practical development of an fuzzy controller that memorize the optimal strategy, executed by the GPC, to regulate the temperature and the CO2 concentration of the greenhouse inside air.

Abstract
The recent new developments in hardware and software tools, and in particular of the microprocessors and microcontrollers, are leading to more complex control and management potentialities in the agriculture applications. For the quality and productivity improvement of greenhouse crops it is necessary to measure and control several interacting physical variables. Also, to achieve competitiveness in the market, the production costs must be kept as low as possible. These tasks can only be accomplished using control and management systems with adequate built in software. At the University of Tras-os-Montes and Alto Douro, Vila Real, a data acquisition and control network was implemented with the aim of being applied to agricultural processes. This network has three main operating levels. At the lower level, a set of remote microcontroller stations performs the data acquisition and transmission by radio frequency to a collecting and control station. The control station generates the actuating signals for the agricultural process and communicates with a higher level network, based on PC's. This higher level network is responsible for the system management and supervision. In this paper it will be described the implemented network and the results achieved in its application to the greenhouse environmental and control.

Abstract
A major transport company working in a urban environment, in Portugal, has been developing an automatic vehicle location (AVL) system, based on a telemetric system to assist the optimisation of vehicle use, time-tabling and scheduling. The data is used in real time and stored on disk for later statistical analysis. Several factors can corrupt data during acquisition and transmission, and make it impossible to automatically extract useful information. A pre-processing stage is needed to extract inconsistent data. The paper describes a strategy, based on simulation, to pre-process the data in order to analyse data consistency and classify the messages as correct or incorrect. Copyright (C) 1998 IFAC.

Abstract
Fuzzy Logic is a part of Artificial Intelligence science and provides for control of complex processes, where exact models are not applicable. Such a controller is necessary for the process of drying oil filled transformers. Indeed, this controller needs to tackle with a highly non-linear and time variant process. The development of the controller was fast and the implementation size very small. Its performance proved very robust whilst providing both good dynamical and steady-state behaviour.