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16.322 Stochastic Estimation and Control, Fall 2004

Graph of variance versus time.
The variance of a state estimate reduced by measurements taken over time. (Image by Prof. Wallace Vander Velde.)

Highlights of this Course

This course features a complete set of lecture notes and readings.

Course Description

The major themes of this course are estimation and control of dynamic systems. Preliminary topics begin with reviews of probability and random variables. Next, classical and state-space descriptions of random processes and their propagation through linear systems are introduced, followed by frequency domain design of filters and compensators. From there, the Kalman filter is employed to estimate the states of dynamic systems. Concluding topics include conditions for stability of the filter equations.
 

Staff

Instructor:
Prof. Wallace Vander Velde

Course Meeting Times

Lectures:
Two sessions / week
1.5 hours / session

Level

Graduate

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