By the end of this course students will be able to:

- know, interpret, and apply the concept of optimality with the following dimensions:
- measures of optimality
- performance indices
- optimality in dynamic systems

- know, find, and interpret and solution of parameter optimization problems with the following dimensions
- problems without constraints
- problems with equality constraints
- Lagrange multipliers
- necessary conditions for a stationary point
- sufficient conditions for a local minimum
- problems with inequality constraints.

- know and apply variational approach to the solution of open loop optimal control problems with the following components:
- calculus of variations, functionals, extremals
- necessary conditions for optimal control
- optimal control as a two-point boundary value problem
- equality constraints on controls and states
- Pontryagin's minimum principle, inequality constraints on controls and states
- minimum time problems
- minimum control effort problems
- singular optimal control

- know and use methods in the solution of optimal feedback control problems with the following components:
- Hamilton-Jacobi theory
- dynamic programming, Hamilton-Jacobi-Bellman equation
- linear systems with quadratic performance indices, matrix Ricatti equation
- regulators and stability.