The project deals with complex systems arising from the composition of many locally controlled subsystems. These systems are interacting and they must be coordinated to achieve a common goal, namely the optimization of a common cost function, while meeting operational constraints defined in terms of control and state variables. The overall dynamic model for such systems is typically known only partially. Besides, the subsystems can be influenced by unpredictable external factors and they can be subject to faults. The aim of the project is to study and develop a management scheme that is able to set the set-point (or the reference trajectory) of each subsystem in order to meet the optimality conditions and the constraints mentioned above, despite the modelling uncertainties and the external disturbances. As an example, let us mention the case of a wind farm. The wake effects induce a coupling between the wind turbines. The aim is to determine the set point of each of them so as to maximize the produced power while limiting fatigue loads, despite the restricted knowledge on the wind velocity field within the wind farm.
The work will be divided in three lines of research:
– set point optimization for constrained and uncertain systems subject to external disturbances through a centralized approach,
– set point reconfiguration upon occurrence of faults, in order to pursue the operation, possibly in a degraded mode,
– development of an approach for set point management able to solve the problems mentioned in the first two lines of research in a decentralized way.
The developed methodologies will be validated on a realistic wind farm simulator on the one hand, and on a cooperating multi-robot system on the other hand.