Machine learning methods have attracted growing interest across many fields, including solid mechanics. Constitutive artificial neural networks (CANNs) have shown high efficiency and accuracy for modeling hyperelastic materials, while physics-informed neural networks (PINNs) provide a data-free alternative to conventional simulation techniques. However, standard PINNs often require large, complex networks and dense sampling in the simulation […]

This seminar presents a systematic methodology for the design of flight control laws for Medium Altitude Long Endurance (MALE) UAV operating at high altitudes, including the development of control law for fully autonomous take-off and landing operations. The process begins by developing a detailed model of the aircraft, incorporating parameters such as mass, inertia, aerodynamic […]