ME507 APPLIED OPTIMAL CONTROL
| Course Code: | 5690507 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Mechanical Engineering |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Prof.Dr. BÜLENT EMRE PLATİN |
| Offered Semester: | Fall and Spring Semesters. |
Course Objectives
At the end of this course, the student will be able to
- gain the basics of the optimal control, both in open loop and closed loop manner,
- emphasize on the theory as well as on real life engineering applications,
- make the physical interpretation of optimal control applications.
Course Content
Parameter optimization. Performance measures. Variational approach to open loop optimal control, Pontryagin's minimum principle. Optimal feedback control, dynamic programming, linear systems with quadratic performance indices, matrix Riccati equation. Numerical solution techniques of optimal control problems.
Course Learning Outcomes
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.