System identification is a vital aspect of modern control and automation, offering a pathway to develop mathematical models from observed input-output data of dynamic systems. This paper explores ...

Sufficient information about system dynamics and inner states is often unavailable to aerospace system controllers, which requires model-free and output feedback control techniques, respectively. This ...

A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system ...