Abstract
Within industrial environments a multitude of different working practices, manufacturing technologies and information systems are continually appearing. Significant benefits can be achieved through integration of the information allowing key decisions to be made based on timely and accurate data. This communication presents the work carried out at an industrial site consisting on the integration of several areas and based on the use of different communication standards. The implementation satisfies several types of requirements, which include not only the functional requirements, but also the preservation of previous investments. The use of OSI (Open Systems Interconnection) based technologies, such as those developed in the aim of CCE-CNMA (CIME Computer Environment by integrating a Communication Network for Manufacturing Applications), contributed to the success of this work.

Abstract
This paper shows that the compositional rule of inference reduces to the compatibility modification inference, when the antecedent of a fuzzy rule and its input fulfil some properties. Two main types of implications are investigated, those generalizing the classical material conditional (residuated and strong implications), called in this paper m-implications, and those generalizing the classical Cartesian product (t-norms and pseudo-conjunctions), called t-implications. For m-implications, when their maximum modus ponens generating function is used, the compatibility measure depends obviously on the relationship between input and antecedent, but also on the t-norm the implication comes from. Similarly, for t-implications, also used as their own modus ponens generating function, the compatibility measure depends again on the input and antecedent, but also on the t-norm they come from. As it could be expected, in the first case the compatibility measure is a degree of the inclusion of the input into the antecedent, while in the second one it is a degree of the intersection of both.

Abstract
This paper describes a computer-based temperature control system for a growth chamber. The system consists of a low cost computer with a data acquisition card acting as the interface between the process and the computer. The software developed has a menu-driven user friendly interface to access execute the functions implemented: choice of the sampling interval, choice of the setpoints, name files, etc.. The user can program up to six different temperature setpoints as constituting six time programmable events along the day. The identification of the thermal process was made from the analysis of the output data collected from the process in response to random generated input signals. Using this model it was possible to establish optimal linear and non linear control strategies in order to achieve the desired setpoint and to minimize the number of actuation. The actuation over the heating and cooling systems were performed with conventional PID and fuzzy controllers and their responses were compared.

Abstract
In this paper climate discrete-time dynamic models for the inside air temperature of two different greenhouses are identified, using data acquired during two different periods of the year. These models employ data from air temperature and relative humidity (both inside and outside the greenhouse), solar radiation, wind speed and control inputs (ventilation, etc.), acquired with a sampling rate of 30s and storage rate of 1 min. Using software developed with Matlab, and its Identification Toolbox, the structure of the dynamic transfer functions is first selected, and its parameters afterwards identified using off-line techniques. Several simulations experiments show that the second-order models identified achieve a close agreement between simulated and experimental data. As different model parameters were obtained for each case studied, implying that the system is time-varying, these models must be obtained in real-time, employing on-line identification techniques. These models will afterwards be used in real-time climate control, where different control strategies will be compared, with respect to set-point accuracy, energy consumption and actuator wear.

Abstract
We show that incoherently coupled soliton pairs are possible in biased photorefractive crystals, under steady-state conditions. These solitons can propagate in bright-bright, dark-dark, as well as in bright-dark configurations. Such soliton pairs can be established provided that the carrier beams share the same polarization, wavelength, and are mutually incoherent. Relevant examples are provided where the photorefractive crystal is of the strontium barium niobate type. The characteristics and stability properties of these soliton states are also discussed in detail. (C) 1996 American Institute of Physics.

Abstract
We investigate higher-order space charge field effects on the evolution of bright spatial solitons in biased photorefractive crystals under steady-state conditions. Numerical simulations demonstrate that these optical solitons can experience considerable increase in their self-deflection especially in the regime of very high bias field strengths. This process is further studied using perturbation techniques. Our analysis indicates, that for very high bias fields, the self-bending process is further enhanced by a factor that varies cubically with the applied field. Relevant examples are provided.