Abstract
This paper describes the goals and some of the results obtained in the project entitled "Computerised Management of Greenhouses", that has started in November 1995. This project has a duration of three years and is sponsored by JNICT (Portuguese Institute for Scientific Research Funding). At present, the experimental set-up is composed of a greenhouse with a floor area of 210m(2) equipped with several actuators and sensors that are connected to an acquisition and control system developed at the Engineering Department of UTAD University. The set-points for the air temperature and humidity, CO2 concentration, soil moisture and ambient radiation inside the greenhouse are calculated on-line as a function of the greenhouse climate, outside weather and the specified optimal set of values for the plants, in this case tomato. The results show that the climate control system performs well and that has been achieved a reduction of the energy consumption compared with the case when the set-points are fixed. In the second year it will be implemented a distributed control system for monitoring and control the environment of four greenhouses located at the University campus. Also, in one of the greenhouses, will be used renewable energies such as the solar photovoltaic and the solar thermal energies. The first is to deliver power to the electronic equipment and to some of the actuators and the second for heating the greenhouses. During this period and the third year it will be implemented and compared different real-time control strategies with respect to set-point accuracy and energy consumption.

Abstract
This paper describes a computer-based temperature control system for an environmental chamber. The identification of the thermal process was made from the analysis of the collected output data in response to random generated input signals. Using this model it was established the optimal linear and non linear control strategies in order to achieve the desired set-point and to minimize the number of actuations. The actuation over the heating and cooling systems were performed with conventional PID and fuzzy controllers and their responses were compared. This work enhances fuzzy controllers application with self-learning capability to achieve the prescribed control objectives in a near-optimal manner. By applying back-propagation through time it was possible to force the plant block to generate the desired trajectory.

Abstract
A real-time parameter estimator for the climate discrete-time dynamic models of a greenhouse located at the North of Portugal are presented. The experiments showed that the second-order models identified for the air temperature and humidity achieve a close agreement between simulated and experimental data. The real-time data acquisition and the recursive identification techniques implemented are used in the simulation and design of an adaptive climate controller to achieve set-point accuracy and minimisation of the energy inputs.

Abstract
For a greenhouse located at UTAD-University, the methods used to estimate in real-time the parameters of the inside air temperature model will be described. The structure and the parameters of the climate discrete-time dynamic model were previously identified using data acquired during two different periods of the year. Several experiments showed that the second-order models identified achieve a close agreement between simulated and experimental data. Afterwards it has been found that parameters change with varying operational conditions. Thus, for a efficient use of these models in real-time control a recursive identification technique for the estimation of the parameters was implemented.

Abstract
The control of manufacturing processes requires the use of a communication infrastructure. Since the object-oriented model is well adapted for the modelling of industrial processes, an ORE seems the logical choice for the communication layer. This paper presents an ORE developed for this purpose, based on DCE services.

Abstract
A major public transport company, working in a urban environment, in Portugal, has adapted a telemetric system for automatic vehicle location, AVL, in order to optimise vehicle use, timetabling and scheduling. The system is able to provide real time location and load of the buses, to exchange voice messages with the driver and to propose preventive maintenance actions on the vehicles. The control centre exchanges messages with all the buses. These messages have two different components: the real-time control component, that is thrown away after use, and the off-line component that has its data stored sequentially on disk, far later analysis. Our main concern is to extract relevant information from this bulk of data to provide the bus management expert with a more accurate knowledge of the bus fleet performance, namely the bus operation efficiency, to improve vehicle use and scheduling. Several factors may corrupt the data that is stored on disk and make it impossible to automatically extract useful information. A pre-processing stage is needed to classify data as consistent or inconsistent. A strategy to implement this preprocess stage has been proposed in a previous paper [Cunha 1997], The idea is based on a virtual bus model. The virtual bus travels on a bus route and recreates the real bus service. It compares messages which have been received with those that could be expected in the model. The model is extended in this paper, in order to analyse inconsistent data and take automatic correction actions. In less common situations, control is passed to a human operator for him/her to make an appropriate correction.