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Instructor: Professor Bjarne Foss
Course description:
The course will give the students an introduction to optimization as a design
principle through theory, examples and assignments. The examples will range
from simple examples to industrial like problems. Optimization in both static
and dynamic systems will be studied. Optimization in dynamic systems will
include both optimal control and Model Predictive Control (MPC).
Contents:
Module 1: Conditions for optimization in systems with constraints (includes
static as well as dynamic systems), Local/global constraints,
Lagrange-formulation, Kuhn-Tucker conditions.
Module 2: Optimization algorithms (search algorithms) for LP, QP and
nonlinear problems.
Module 3: Optimal control without inequality constraints, the LQ-problem and
the Riccati-equation. Focus on discrete time systems.
Module 4: Model Predictive Control (MPC)
Prerequisites:
Mathematics 1-4, TTK4105 Control Systems, TTK4115 Linear System Theory
or corresponding courses
Form of instruction: Lectures,
exercises and compulsory project work
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