Introduction: Simulation classification – Objectives, concepts, and types of models – Modeling: 6- DOF models for aerospace vehicle with prescribed control surface inputs – Control Systems: Mechan- ical (structural), Hydraulic systems and their modeling – Block diagram representation of systems – Dynamics of aerospace vehicles – Pilot station inputs – Cues for the Pilot: Visual, biological, and stick force – Virtual Simulation: Fly-by-wire system simulation – Uncertainty Modeling & Simula- tion: Characterization of uncertainty in model parameters and inputs, use of simulation to propagate the uncertainty to system response, Monte Carlo simulation – Simulation of stiff systems – Differential algebraic equations – Applications: Modeling and simulation methodologies for a complex engineering system simulation, aerospace system simulation – Model Building Techniques: Parame- ter identification, system identification – Least square estimation, maximum likelihood estimation, Kalman filters, neural networks.

Same as Reference

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