Stochastic Estimation and Control

Graph of variance versus time.

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


MIT Course Number


As Taught In

Fall 2004



Cite This Course

Course Features

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.

Wallace Velde. 16.322 Stochastic Estimation and Control, Fall 2004. (Massachusetts Institute of Technology: MIT OpenCourseWare), (Accessed). License: Creative Commons BY-NC-SA

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