Foto Trofino

Alexandre Trofino

Full Professor
 CNPq resercher
Universidade Federal de Santa Catarina (UFSC)
Departamento de Automação e Sistemas (DAS)
DAS/CTC-UFSC Campus Trindade
88.040-900 Florianópolis, SC, Brasil
Tel.: (+55)(48) 3721 7699
Secretaria: (+55)(48) 3721 9934


Bacharel in Electrical Engineering from the Universidade Catolica de Petropolis, Brazil, December 1981, Master in Automation from the Universidade Estadual de Campinas, Brazil, June 1985 and Doctor in Automation from the Institut National Polytechnique de Grenoble, France, January 1993.  He is full professor of the Department of Systems and automation, Federal University of Santa Catarina, Brazil. He is coordinator of the Project UFSCkite, pioneer in Latin America in developing technologies for Airborne Wind Energy. He conducts research in the area of energetic efficiency and control of refrigeration systems in collaboration with researchers from Polo laboratory. He also investigates and develops techniques for Brain-Machine Interface and is a member of a multidisciplinary team, including neuroscientists, psychologists and engineers, interested in studying techniques of deep brain stimulation for the treatment of brain illnesses. He is author of an awarded thesis and paper.



Renewable energy: Wind turbines based on tethered airfoils

  Aerofólio Cabeado
Legend: Field test of flight control of an UFSCKite prototype.


Wind turbine based on tethered airfoil is a new paradigm to exploit the eolic energy having several advantages over the conventional technology based on tower and blades. There are several possible configurations for this new technology. In the simpler one the electric generator is placed on the ground, the tower is replaced by a tether and the blades by an airfoil (similar to a paraglider). This allows for a drastic reduction in the construction, installation and transport costs of the wind turbines. Moreover, the use of tether allows for the airfoil to operate in higher altitudes (600 meters), where there are stronger and more frequent wind that are not exploitable by the conventional tower based technology. By operating in higher altitudes, this new technology can exhibit economic viability even in places where the conventional technology is not attractive due to insufficient wind conditions in lower altitudes. This aspect allows, for instance, to reduce costs associated with long transmission lines by installing these new generation units near the main consumer centers. From the environmental point of view, one advantage of this new technology is the possibility of moving the airfoil operation away from the birds migration routes to avoid collisions, which is not possible with the conventional wind turbines without stopping operation. The Federal University of Santa Catarina is pioneer in Latin America in developing this new technology. The UFSCkite laboratory is developing 12Kw prototypes, currently under final indoor tests, and a low cost measurement unit, based on a drone and acoustic tomography, to find suitable places to install this new technology. Several studies, from under graduation level to master, doctorate and post-doc levels, were conducted in the UFSCkite laboratory leading to several international publications with possibility of establishing patents associated to the innovative solutions found by the UFSCkite team. Learn more



Brain-Machine Interface

  Interface cérebro-máquina

 Brain-Machine Interface is a type of connection between brain and machine that allows for the machine to be controlled trough signals expressing the brain activity. Research in this area has received huge investments, like for instance the investment in the new Elon Musk's enterprise Neuralink. The first step to establish an interface is to get information from the brain activity, as for instance  through sensors of electroencephalogram placed on the scalp. The signals that come from these sensors are filtered for noise reduction and elimination of artifacts (patterns that are present in the brain activity and are not of interest to the ongoing analysis). Next, the signals are precessed to highlight the desired characteristics, i.e., to reinforce signal patterns that are always present in the type of task we would like to recognize in the brain activity. For instance, if the task is movement of the left hand we should highlight the energy of the signals that come from the right motor cortex in a certain frequency band. The processed signal is then classified into classes that specify the tasks we would like to recognize in the brain activity. Each time an EEG signal is classified, a command signal is applied to the machine in order to enforce a desired response. Each class is associated with a different command. For instance, the command drives a wheelchair to the left if the task recognized in the signals is classified as movement of the left hand. The movement can be a real or just imagination, because both tasks will produce similar activity in the right motor cortex. Brain-machine interface tools can be used to face several problems, from driving vehicles to computer games and medicine applications. Of particular interest there are medicine applications where the human body plays the role of the machine that should be controlled in order to correct some undesired states, like stress or illness of the type epilepsy among others. Master and PhD studies carried out in this area in the Department of Systems and Automation have focused in the development of strategies for driving a drone through a given trajectory using motor imagery and classifying levels of stress from EEG and ECG signals. Some works involving classifying levels of anxiety and deep brain stimulation in rats were performed in collaboration with a multidisciplinary team of neuroscientists and psychologists from the Post Graduate program in Neuroscience at UFSC.  Saiba mais





Energy Efficiency and Temperature Regulation: Control Techniques for Refrigeration Systems

  Sistema de refrigeração
Legend: Test stand in Polo with automatic door opening system and controlled environment.


According to a research,  almost all brazilian homes have refrigerators which were responsible for approximately 6% of the total energy consumption in Brazil in 2010. Due to their large number, even a small efficiency improvement in these devices could lead to a enormous reduction in the energy consumption of the country. For this reason, more stringent norms for energy efficiency have been adopted for various countries leading refrigerator manufactures to improve the efficiency of their products. Moreover, keeping the temperature in the refrigerator and freezer compartments at their correct values is an important issue to the quality of the food inside the compartments. Simple refrigerator models are the most popular but, in general, exhibit a bad temperature regulation and low energy efficiency due to economical constraints associated with prices of these devices. Recall that an improper food conservation in refrigerators are often mentioned as a source of food intoxication. The difficulty of keeping regulated the temperatures is even more critical due to the frequent door openinings and introduction of hot food inside the compartments. In this context, the use and improvement of control techniques in refrigeration systems has a great potential to be explored either in temperature regulation or energy efficiency problems. Research activities in this area at the Department of Systems and Automation are carried out in collaboration with researchers at  Polo, Laboratory for Emerging Technologies in Cooling and Thermophysics at UFSC, where the students perform their experimental set up.