Selected Projects


Design and realization of robotic systems such as mobile robots and Unmanned Aerial Systems (UAS) are conducted in the IRES research group. The aim of this research is to develop cooperative multi robot learning and adaptive control methodologies. In the absence of a leader, each robot navigates independently.

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Electric Machine Drives

IRES facility is equipped with various types of electric machines and industrial drives. The research focuses on the development of advanced drives mainly for Permanent Magnet Synchronous Machines (PMSM) and Induction Machines (IM). The aim of this research is to develop the next generation of machine drives.

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Energy Conversion

Innovative energy conversion systems are instrumental in meeting future energy needs. In this regard, a variety of advanced control strategies are implemented on different types of converters: three-phase rectifiers, three-phase inverters, matrix converters, and DC/DC converters.

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Research Philosophy


The diversity of expertise is a crucial aspect in the development of complex technologies. Our research philosophy promotes team work to face the complexity of research areas allowing the complementarity of resources and research infrastructure. This strategy yields rationalization of resources and a more effective response to common needs, including specific top-class training. It also contributes to accelerate the advancement of knowledge and technology transfer to industry.

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In most existing robotic systems, maximizing stiffness to minimize vibration and achieve good position accuracy of robots is a key element in their design. This high stiffness is achieved by using heavy material and a bulky design. Hence, the existing heavy rigid robots are shown to be inefficient in terms of power consumption and operational speed. In order to improve industrial productivity, reducing the weight of the arms and increasing their speed of operation are required. Therefore, light-weight robotic systems have received a thorough attention lately, thanks to their larger work volume, better maneuverability, higher operational speed, power efficiency, lower cost, and larger number of applications. However, controlling such systems still faces numerous challenges that need to be addressed before they can be used in abundance in everyday real-life applications. The severe nonlinearities, varying operating conditions, structured and unstructured dynamical uncertainties, and external disturbances, are among the typical challenges to be faced with when dealing with such often ill-defined systems.


AC machines proved to be the solution to application which requires high torque density, high precision, wide speed range and efficiency such as electric vehicles and wind turbines. Although these machines are designed to produce high torque per volume and constant power over wide speed range, achieving all of these benefits underlays the proper optimum control system based on the behavior of the machines. Since they can be used in various applications, their performance is limited to unknown uncertainties, such as load torque variations and external disturbances. Therefore, an advanced control method is required to utilize them at the best of their performance.


In the last decade, alternative energy sources such as renewable energies have received a thorough attention and have been considered as a way of fighting climate change. Among renewable energies, wind turbine has become the world's fastest growing energy generator. Variable speed wind turbines are widely used in many high performance applications and offer several advantages with respect to their fixed speed counterpart, such as maximum power extraction from the wind and reduced power electronics requirements and costs. Thus, a variable speed generator achieves optimal energy generation by adjusting its rotational speed to track wind speed. However, wind turbine dynamics is highly nonlinear and wind speed is continuously variable and unpredictable. The conflicting requirements between the nature of wind and optimal energy generation make the wind turbine control task a challenging research problem. Typical challenges include varying operating conditions, high nonlinearities, and external disturbances. This raises the urgency to consider alternative approaches for efficient power generation to keep up with the increasingly energy demand requirements.