ME 224 System Identification and Estimation



Deterministic state estimation, recursive observers, estimation for uncertain process dynamics; SISO and MIMO least-squares parameter estimation, linear system subspace identification. Random variables and random processes: linear systems forced by random processes, power- spectral density. Bayesian filtering including Kalman filter. Jump- Markov estimation and fault diagnosis. Nonlinear estimation, particle filters, unscented Kalman filter. Introduction to estimation for hybrid systems.
Course period02/5/11 → …
Course level200