Course - Numerical optimal control - TK8115
Numerical optimal control
New from the academic year 2012/2013
About
About the course
Course content
Advanced topics and numerical methods for optimal control problems form the core of the curriculum. This includes ways to formulate optimal control problems, numerical methods and software to solve them, and analysis of their performance and properties from a control and numerical point of view.
Learning outcome
Knowledge
- Thorough understanding of the methods and theoretical foundation for direct methods for formulation of nonlinear optimal control and model predictive control as numerical optimization problems, in particular related to stability, robustness, feasibility and numerical properties.
- Basic understanding of indirect methods for optimal control, such as Pontryagin´s maximum principle and the theory of dynamic programming.
- Basic understanding of numerical methods for optimization, in particular quadratic programming, semi-definite programming and nonlinear programming.
- Basic understanding of numerical linear algebra theory for solving optimization problems (QR, LU, Schur,
)
- Basic understanding of methods that use integer variables for formulation of optimization problems for the use of mixed-integer linear programming.
- Basic understanding of semi-definite programming and linear matrix inequalities, and their use in optimal control formulations.
- Basic knowledge of the theory of parametric programming and its use in explicit MPC.
Skills
- Ability to formulate well-conditioned optimization problems in standard forms
- Proficiency in use of numerical software for convex and nonlinear programming
- Knowledge of mathematical modeling tools for numerical optimal control
- Ability to select linear algebraic methods in order to exploit structural properties such as sparsity and band structure.
Transferable skills
- Presentation of advanced scientific topics, and scientific discussion (colloquia)
- Scientific writing skills (project report)
Learning methods and activities
The course is based on a combination of lectures, colloquia where students present topics, and a project.
Recommended previous knowledge
TTK4130 Modelling and Simulation
TTK4135 Optimization and Control
TTK4150 Nonlinear Systems
Course materials
Information will be given when the course starts.
Subject areas
- Engineering Cybernetics