Robust and adaptive control design for nonlinear systems with applications to robot manipulators and aerial robots

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This project deals with adaptive and robust control design for nonlinear systems with applications to robot manipulators and unmanned aerial vehicles (UAV's). The first problem that we would like to tackle, during the course of this project, is the design and real-time implementation of some robust and adaptive iterative learning controllers (ILCs) for industrial robot manipulators performing repetitive tasks (e.g., automotive manufacturing industry). In particular, we would like to tackle some of the technical and practical limitations in ILC design, which prevent ILC techniques from being fully exploitable in practical applications. The second topic that we would like to address, during the course of this project, is the robust attitude stabilization of vertical take-off and landing (VTOL) aerial vehicles such as the quadrotor and the ducted-fan aircraft. In fact, being able to design a VTOL-UAV, which is highly maneuverable and extremely stable, is an important contribution to the field of aerial robotics since potential applications are tremendous ( e.g., exploration of hazardous environments, high buildings and monuments investigation, rescue missions, film making, etc). One of the main challenges in achieving such an objective is the elaboration of efficient low-cost sensors and processing techniques for the attitude measurement/estimation, as well as the development of efficient control laws. The expected high-quality theoretical research, supported by practical applications, will increase the state of the knowledge in modern control engineering. Moreover, the proposed research project will provide opportunities for excellent training of high-qualified professionals in challenging and promising research fields.