|Dr. Brad Burchett|
|Dept. of Mechanical Engineering|
|Office: C-107 Moench Hall|
|Office Phone: 877-8929|
No textbook is required, however the following references are suggested, most of which are freely available online:
Computational Intelligence in Control Engineering, by Robert E. King, Dekker, 1999. The book is currently out of print, however many used copies are available online, and one copy is reserved at the library.
Genetic Algorithms in Search , Optimization, and Machine Learning, by David E. Goldberg, Addison Wesley, 1989. Available in the Library
Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities, by Frank L. Lewis, Javier Campos, Rastko Selmic, SIAM Press, 2002.
Robust Control Systems with Genetic Algorithms, by Mo Jamshidi, et al., CRC Press, 2003.
Adaptive Fuzzy Systems and Control, by Li-Xin Wang, Prentice Hall, 1994.
Ben J.A. Krose, P.Patrick van der Smagt, An Introduction to Neural Networks, Univesity of Amsterdam, Faculty of Mathematics Computer Science , January 1993.
S. N. Sivanandam, and S. N. Deepa, Introduction to Genetic Algorithms, Springer.
There is also a great deal of info on the web regarding Neural Networks. See the links page for these.
Five homework sets will be issued during the quarter. These problem sets are intended to deepen understanding of the material. The homework set grade is a substantial portion of the course grade and should be addressed accordingly.
Two projects will be assigned. These required significantly more effort than the homework set, and as such count for 50% of the final grade.
Grades in ME 536 will be determined based on proficiency on Homework Sets, and Term Projects. and In-Class Quizzes. There are no exams in ME 536. The relative weighting of each graded event is shown below:
|Homework Sets||500 pts|
|Term Projects||500 pts|
Occasionally, students will be offered the opportunity to obtain extra credit points. These points are added to the student's total while the total points for the course remain at 1000.