ANGELO ALESSANDRI

Effectiveness of data-driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one-hidden-layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state...

Autonomous ships represent one of the new frontiers of technological innovation in marine engineering, which demand the development of innovative control systems to guarantee efficient and safe navigation of vessels. A convenient control system should be able to command the several actuators installed on board in different conditions—for...

We investigate wellposedness and stability of normal flow equations with two different control schemes. The first one considers the velocity field as a control action and relies on a proportional regulator that is proved to be stable. In the second one, control acts on the source term and is based on an observer providing an estimate of the...

Electromagnetic actuation can support many fields of technology, such as robotics or biomedical applications. In this context, fully understanding the system behavior and proposing a low-cost package for feedback control is challenging. Modeling the electromagnetic force is particularly tricky because it is a nonlinear function of the actuated...

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