Abstract
This work presents an automatic tuning method for the discontinuous component of the Sliding Mode Generalized Predictive Controller (SMGPC) subject to constraints. The strategy employs Particle Swarm Optimization (PSO) to minimize a second aggregated cost function. The continuous component is obtained by the standard procedure, by Quadratic Programming (QP), thus yielding an online dual optimization scheme. Simulations and performance indexes for common process models in industry, such as nonminimum phase and time delayed systems, result in a better performance, improving robustness and tracking accuracy.

Abstract
This work presents the use of a genetic algorithm to design a Mandani Fuzzy Controller with two inputs and one output, written in Matlab (R) environment, applied to a two axis positioning system using a robot. The robot has 6 degrees of freedom and is controlled with the objective of capturing an object on a workspace using a fuzzy controller. A genetic algorithm is used in order to determine the main characteristics of the membership functions of the fuzzy controller. The complete system employed to simulate the two axes positioning system uses the Transfer Function of two axes of the robot and the Fuzzy controller. In this work was implemented and simulated an operating scenario, being the results and the performance of the controller presented regarding the controller energy effort and the evolution of the (x,y) trajectories over time.

Abstract
Aging of Tawny Port wine is a multifactorial process critical for attaining the desired quality. Real time monitoring of important intrinsic and extrinsic factors that are known to affect the time and quality of the aging process are important to optimize and to manage the natural variability between wines aged in different long used wood barrels. For this study, a distributed monitoring system was installed in sixteen oak barrels, placed in two adjacent wineries - one of them with controlled temperature in the Douro Demarcated Region, Portugal. The monitoring process was performed using a RS-485 industrial network, which interconnects sensors that continuously measure wine temperature, pH, redox potential and wine's dissolved oxygen, as well as other sensors that measure parameters related to the barrels' environmental context, such as room temperature and relative humidity. This work presents the design, development and implementation of a remote distributed system to monitor such parameters, aiming to determine the existence of behaviour models for Port Tawny wine during aging in long-used oak barrels, depending on their storage history and to understand the evolution of wine pH, dissolved oxygen and redox potential in real winery conditions as well as their dependence on the wine's storage temperature. This approach is based on easy-to-use embedded systems, with the aim of giving a relevant contribution to other projects in the area of precision enology.

Abstract
Despite the studies already developed about Trombe walls, more research work is needed to contribute to the knowledge about their behaviour and optimize it according to the specific characteristics of each climatic region. The ventilation openings and the shading device operation decisively influence the temperatures fluctuation along the system and that impact should be discussed. In this context, a test cell with a classical Trombe wall was submitted to real climatic conditions in a Portuguese city. The effect of ventilation openings and shading devices in the temperatures fluctuation was analysed. The temperatures in the air layer and along the massive wall presented a similar oscillation pattern and exceeded 60 degrees C without ventilation and shading devices. For this configuration, temperature values at the top of the air layer were always higher than those obtained at the base and a differential of 19 degrees C was achieved. The temperature fluctuation across the massive wall was not proportional to its thickness due to its heat storage capacity. When the ventilation system was closed and the shading device was not activated, the temperature inside the test cell exceeded the outside temperature value in 9 degrees C, showing the system ability to store and release heat.

Abstract
This paper provides a bare-bone introduction to evolutionary and bio-inspired metaheuristic in the context of environmental greenhouse control. Besides presenting general evolutionary algorithm principles, specific details are provided regarding the genetic algorithm, particle swarm optimization and differential evolution techniques. A review of these algorithms within greenhouse control applications is presented, both for single and multiple objectives, as well as current trends.

Abstract
The point prediction quality is closely related to the model that explains the dynamic of the observed process. Sometimes the model can be obtained by simple algebraic equations but, in the majority of the physical systems, the relevant reality is too hard to model with simple ordinary differential or difference equations. This is the case of systems with nonlinear or nonstationary behaviour which require more complex models. The discrete time-series problem, obtained by sampling the solar radiation, can be framed in this type of situation. By observing the collected data it is possible to distinguish multiple regimes. Additionally, due to atmospheric disturbances such as clouds, the temporal structure between samples is complex and is best described by nonlinear models. This paper reports the solar radiation prediction by using hybrid model that combines support vector regression paradigm and Markov chains. The hybrid model performance is compared with the one obtained by using other methods like autoregressive (AR) filters, Markov AR models, and artificial neural networks. The results obtained suggests an increasing prediction performance of the hybrid model regarding both the prediction error and dynamic behaviour.