In recent years we have witnessed the emergence of many autonomous and intelligent devices. Home appliances like automated vacuum cleaners and lawn mowers, as well as delivery drones and self-driving cars, just to name a few, are examples of how smart systems are becoming part of our daily lives. Roughly speaking, a smart system should be able to collect data through sensors and interact with the environment by means of actuators, in a way that emulates intelligent behavior.
Unlike conventional mechatronic systems, such as industrial robots, which operate in a well-structured environment and perform repetitive tasks, smart systems have to deal with a high level of uncertainty and adjust their behavior according to both internal and external changes. Moreover, although traditional control schemes have been successfully employed in robotic manipulators and other industrial applications, they may not represent the most suitable choice for systems subject to a wide variation in their operating conditions. On the other hand, because of their ability to learn from experience by interacting with the environment, machine learning and soft computing techniques are commonly used when uncertainties and imperfect information must be taken into account.
The main directions of our current research in smart systems are outlined below.
Intelligent control: Intelligent controllers play an essential role in the design of more precise and energy-efficient smart systems, resulting in more safety, productivity, and sustainability. Combining modern nonlinear control techniques (sliding modes, adaptive methods and feedback linearization) with soft computing and machine learning algorithms (artificial neural networks, fuzzy logic, reinforcement learning and Gaussian process regression), it is possible to design control strategies capable of dealing with the uncertainties and external disturbances inherent to the unstructured world in which we live.
Autonomous systems: By interacting more closely with humans, smart systems will increasingly face unexpected situations that could not have been foreseen by their designers. In this way, autonomous systems must be able to make quick decisions and still respect the moral and ethical issues of our society. This exciting research area is at the fore front of technological development and also offers the possibility of dealing with a multidisciplinary scientific topic, ranging from biologically inspired questions to important philosophical aspects.
For more details, check out [Research].
We are also responsible for the Smart Systems track of the Master’s Degree Programme in Mechanical Engineering. In order to meet the current demands of modern industry, the Smart Systems track gives access to courses in robotics, machine learning, intelligent control, digital factory, systems engineering and modeling, among others. This interdisciplinary approach offers a wide range of cutting-edge knowledge in smart technologies and helps professionals step through the doors of the fourth industrial revolution.
For more details, check out [Teaching].