Optimal and Robust Control
BE3M35ORR + B3M35ORR + BE3M35ORC
This course is part of an already archived semester and is therefore read-only.
Section outline
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(Mathematical) optimization – modeling and analysis
Classes of optimization problems
- Linear programming
- Quadratic programming (with linear constraints)
- Conic programming (linear, quadratic with quadratic constraints, semidefinite, ...)
- Nonlinear programming
(Re)formulations of optimization problems
- Tips and tricks
- Absolute values, max elements, ...
- Using software
- Matlab: CVX, Optimization Toolbox, YALMIP
- Julia: JuMP, Convex
- Python: cvxpy
Conditions of optimality (derivative-based, necessary, sufficient)
- Unconstrained optimization
- Gradient
- Hessian
- Constrained optimization
- Lagrangian, Lagrange multipliers, Projected Hessian
- KKT conditions