ENSE622

Prerequisite: Permission of ENGR-Institute for Systems Research; and ENSE621. Recommended: Familiarity with calculus, probability, linear algebra, differential equations, & computer programming recommended. Credit only granted for: ENPM642 or ENSE622. This course continues the model-based approach to systems engineering by introducing students to a variety of mathematical modeling and simulation techniques used to perform system performance, optimization, and trade-off analyses. Topics include: linear and integer programming; state machine models of finite state machines; development of simple intelligent agents; modeling Markov processes; queueing theory; multi-objective trade-off analyses; decision trees; stochastic (Monte Carlo) simulation, linear regression, some predictive analytic techniques; and an introduction to control theory. Mathematical models and simulations are developed and executed using MATLAB. The course includes a class project in which students solve a problem of interest to them using one or more of techniques addressed in class. Cross-listed with ENPM642. Credit granted for ENSE622 or ENPM642