Modeling and Simulation (M&S) have become important tools for analyzing and designing complex systems in a broad array of disciplines ranging from business and engineering to biology and psychology. For example, in engineering design, M&S can be used to evaluate the effectiveness of a new product concept, verify whether all the functional design specifications are met, or suggest modifications for improving the manufacturability of a product. By using simulations in this fashion, designers can achieve significant reductions in design cycle time and overall lifetime cost of new products. In other disciplines, simulations allow us to perform experiments that cannot be realized in the real world due to physical, environmental, economic, or ethical restrictions. However, simulations are only meaningful if the underlying models are adequately accurate and if the models are evaluated using the proper simulation algorithms. To accomplish this, a systems engineer requires a variety of knowledge and skills in different disciplines. In this course, students will learn about different modeling and simulation techniques and how they can be used in real-world systems engineering problems. They will learn to develop system-level simulation models of both energy-based systems (continuous time) and discrete event systems (DEVS). Through course projects, the students will obtain hands-on experience in modeling and simulation of complex multi-disciplinary systems. The students will perform an entire simulation study of a multi-disciplinary system, from requirements definition and modeling, through simulation and analysis of the results.
In this project course students form interdisciplinary teams, each of whose goal is the design of a product. Industry and government (often local) help us to define projects of real interest to them. They also help with their time and financial support. While projects typically run for two semesters, students can take the course for one or two semesters, as their schedules allow. Students must consider many issues for their products -- What are the product opportunities? What makes their product special? How must it look and feel? Is it technically legitimate? Can it be manufactured economically? How should it be marketed?
The goals of this introductory course in robot control are:
To obtain practical experience generating robot control algorithms, the students will
implement several robot controllers using MATLAB. These controllers will be tested on
simulated robots that have been modeled to include many real-world phenomena such as
friction, sensor noise, and higher order dynamics.
Last modified: Wed May 31 18:47:07 EDT 2000