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

Same as Reference

1. Ogata, K.,System Dynamics, 4th ed., Pearson Education (2004).

2. Doebelin, E. O.,System Dynamics: Modeling, Analysis, Simulation, Designs, MarcelDekker (1998).

3. Ljung, L.,System Identification: Theory for the User, Prentice Hall (1987).

4. Jategaonkar, R., V.,Flight Vehicle System Identification: A Time Domain Methodology,AIAA Progress in Aeronautics and Astronautics, Vol. 216 (2006)

5. Klein, V. and Morelli, E, A.,Aircraft System Identification: Theory and Practice, AIAAEducation Series (2006).