Stochastic Filtering and Control Theory

Course Description

This is an advanced level graduate course with emphasis on theory of stochastic processes and its applications in engineering, finance and statistics. The objectives are to develop a fundamental understanding of stochastic processes and its applications in the area of filtering and control of dynamical systems, to develop an appreciation for the strengths and limitations of state-of-the-art numerical techniques for nonlinear filtering and control problems, to reinforce knowledge in stochastic systems with particular emphasis on nonlinear and dynamic problems, and to learn to utilize stochastic system analysis methods as research tools. Topics include continuous and discrete time random processes; spectral representation; Karhunen-Lo eve Expansion, Martingales, Poisson Processes, Markov processes; It^o calculus; Stratonovich Integral; Kolmogorov equation; linear and nonlinear filtering methods; stochastic optimal control and Hamilton-Jacobi-Bellman equation.

Code

MAE 680

Credits

3

Subject

Mechanical & Aerospace Engr