Introduction to mathematical physics, fall 2013
Introduction to Optimal Control
The aim of the course is to provide an overview of methods and applications of deterministic
and stochastic control theory to mechanics and statistical physics. The course will start by
recalling basic concepts from variational calculus (Euler–Lagrange and Hamilton equations).
It will then proceed with an elementary introduction to Pontryagin theory for optimal control
of systems governed by differential equations. After an heuristic introduction to stochastic
systems, the aim of the second part of the course is to expound the basic ideas of optimal
control of system governed by stochastic differential equations.
The course is intended for advanced undergraduate students of mathematics, physics, chemistry
and mathematical economics. Prior courses in advanced calculus and linear algebra are
required (Diff.Int. 1-2 and Lineaarialgebra 1, or Mapu 1-2). Background material will be on
request discussed during the course
Weeks 36-42 and 44-50, Tuesday 14-16 in room C124, and Friday 14-16 in room C123.
First lecture Friday September the 6th in C123
The course will mainly follow
Lawrence Craig Evans, "An Introduction to Mathematical Optimal Control Theory" Berkeley lecture notes
Other useful references may be
- Ramon van Handel, "Stochastic Calculus and Stochastic Control" Caltech Lecture Notes
- Leonard Christopher Gordon Rogers, "Duality in constrained optimal investment and consumption problems: a synthesis" Paris-Princeton Lectures on Mathematical Finance
- Wendell Helms Fleming and, Mete Halil Soner, "Controlled Markov processes and viscosity solutions" Springer 2006.
- Anastasios G. Malliaris and William A. Brock, "Stochastic methods in economics and finance" Elsevier Science 1999
- Fwu-Ranq Chang, "Stochastic optimization in continuous time" Cambridge University Press 2004
Did you forget to register? What to do?