italian version

Aims :

To provide students with advanced techniques for the optimal control of stochastic systems.

Topics :

- Elements of probability theory and stochastic processes.
- Minimum variance estimate. Orthogonal projection lemma.
- The Kalman filter. Optimal smoothers and predictors.
- Least square identification of dynamic processes.
- Optimal minimum variance control.
- Adaptive control.
- Optimal linear, quadratic, gaussian control.


Textbooks :

- Lectures notes.

- A. Jazwinski, “Stochastic Processes and Filtering Theory”, Academic Press, N.Y. ,1970.

- A.P. Sage, J. Melsa, “Estimation Theory with Applications to Communications and Control”, Mc- Graw-Hill, N.Y., 1971.

- A. Gelb, “Applied Optimal Estimation”, The Analytic Sciences Corporation, Cambridge, 1974.

- P.E.Wellstead, M.B.Zarrop,”Self-tuning Systems”, John Wiley & Sons, Chichester, 1991.

- R.Iserman, ”Digital Control Systems”, Vol. 2, Springer-Verlag, Berlino, 1989.

- F. Lewis, ”Applied Optimal Control & Estimation”, Prentice-Hall, Englewood Cliffs, 1992.

- B.D.O.Anderson, J.B. Moore,”Optimal Control, Linear Quadratic Methods”, Prentice-Hall, Englewood Cliffs, 1989.

- H. Kwakernaak, R.Sivan,”Linear Optimal Control Systems”, Wiley-Interscience, N.Y., 1995.

Exam :

The final examination consists of an oral test. Usually, ther first question needs a written answer.

Tutorial Session :

Everyday upon telephone appointment.