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Abstract
Robust control theory addresses the problem of analysing and designing feedback systems that achieve performance objectives in the presence of uncertainty in the dynamics of the system. Convex optimisation forms the basis of the computational tools needed to solve these problems. The course covers the theory, computation, and practical applic. of these methods to a variety of uncertain systems.
Objective
To introduce students to the basic concepts in robust control and provide them sufficiently familiarity with the computational tools required to design robust controllers with verifiable characteristics in a variety of engineering system domains.
Content
An optimization based approach to robust control theory and applications. Topics will include: H-infinity and H-2 control design; structured-singular value analysis and synthesis; model reduction; convex optimization; semi-definite programming; and interior-point methods.
General Information
- Language
- English
- Levels
- DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture |
Robust Control and Convex Optimisation
Does not take place this semester.
|
No time listed | 2 h weekly |
| exercise |
Robust Control and Convex Optimisation
Does not take place this semester.
|
No time listed | 1 h weekly |
Offered In
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Tracks (all): Electives (Courses from the ETH course catalogue may be chosen in agreement with your tutor. As an alternative to the elective courses, students may do a second semester project or an internship in industry. Please consult your tutor.)
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Doctorate Information Technology and Electrical Engineering (A minimum of 12 ECTS credit points must be obtained during doctoral studies (also see sub-categories for details) More Information at )
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Subject Specialisation (The courses on offer below are but a small selection out of a much larger available number of courses. Please discuss your course selection with your PhD supervisor.)
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Deep Track Courses (At least 20 credits must be completed within the deep track courses. Surplus credit points can be counted towards the electives.)
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Deep Track Robotics (These courses can be credited either as a specialization subject or as an elective subject.)
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