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Aerospace Engineering


GPS Technology Laboratory (Graduate)  
The GPS Technology Laboratory provides an overview of the elements of satellite-based navigation, centered on six lab projects and an individual project. It is by nature an interdisciplinary course, covering subject material in orbit prediction, satellite systems, signal processing, error modeling, computer programming, and digital and microwave electronics.

Professor Name: Penina Axelrad
Department: Aerospace Engineering Sciences
University: University of Colorado

Submitted: Aug 17, 2007
Feedback Control Experiments - Experiments for feedback control education and research  
Quanser Consulting, Inc., offers a complete line of feedback control experiments. The systems are robust, durable, and modular thus allowing you to reconfigure the same plant to obtain various experiments. Our experiments include the Inverted Pendulum, the Ball and Beam, the Seesaw/Pendulum MIMO experiment, and the Helicopter. All systems are equipped with quick-connect cabling, source code in C, handbooks, system modeling, and control system design files written in Maple, MATLAB, and Simulink. Capture your students' interest while teaching them well-established principles or give your research project an edge by implementing the new control strategies you are developing.
Submitted: Mar 13, 2008
Nonlinear F-16 Fighter Model  
Description: This file contains the nonlinear model of an F-16 figheter aircraft in MATLAB/Simulink. High and low-fidelity aerodymaic data are available. A trim function is also included.
Target audience: Graduate
Academic institution: Aerospace Software and Technology Institute
Materials available: Downloadable code/data files
Products: Simulink,Aerospace Blockset

Submitted: Jul 08, 2008
Computational Methods in Aerospace Engineering  
Description: This course serves as an introduction to computational techniques arising in aerospace engineering. Applications are drawn from aerospace structures, aerodynamics, dynamics and control, and aerospace systems. Techniques include: numerical integration of systems of ordinary differential equations; finite-difference, finite-volume, and finite-element discretization of partial differential equations; numerical linear algebra; eigenvalue problems; and optimization with constraints.
Course material created by Professor David Darmofal.
Target audience: Advanced undergraduate (3rd or 4th year)
Institution: Massachusetts Institute of Technology
Materials available: Problem sets or projects, Course outline or syllabus, Downloadable code or data files
Products: MATLAB

Submitted: Jul 22, 2008

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