In this page, you can find information on the courses I teach as part
of the
academic staff at the Department of Electrical and Electronics
Engineering
at Middle East Technical University.
Graduate Courses
EE780 Statistical Techniques in Mobile Robotics
Introduction to statistical problems in mobile robotics. Recursive state
and parameter estimation. Probabilistic robot motion; actuator and
motion models. Probabilistic robot perception; sensor models. Gaussian
and non-parametric filters for estimation. Localization and Mapping
problems. Simultaneous localization and mapping (SLAM) formulation.
Introduction to probabilistic planning and control.
Fall Term 2008-2009 [Syllabus]
Fall Term 2009-2010 [Syllabus]
Fall Term 2010-2011 [Syllabus]
Fall Term 2011-2012 [Syllabus]
Fall Term 2012-2013 [Syllabus][Course Web Site] (Web site open for Registered Students)
EE501 Linear System Theory I
Linear spaces: fields, linear independence, basis, direct sum
decomposition, normed linear spaces, convergence concepts, Banach
spaces. Linear transformations: null and range spaces, matrix
representation, block diagonal form. Linear transformations defined by a
square matrix characteristic and minimal polynomials, direct sum
decomposition of Cn, Jordan canonical form, functions of a square
matrix. Hilbert spaces: inner product, concept of orthogonality,
Hermitian matrices, projection theorem, systems of linear algebraic
equations, general Fourier series
Review of dynamical system models, classification of equilibrium
solution. Results on 2-dimensional systems; Poincare-Bendixon theory for
limit cycles. Liapunov theory; definitions of stability and
applications to linear and nonlinear feedback systems. Input/output
stability; definitions and derivation of frequency response criteria for
stability.
Machine intelligence is an exciting and rewarding field with powerful
foundations to solve real problems in both engineering and other
disciplines. In this course, I aim to equip the students with a solid
foundation on these tools and techniques so as to enable them to apply
AI in their chosen research field. I also aim to stimulate the students
to the presence of research topics in this area itself.
This is a sequence of two consecutive courses forming a whole capstone
design course. It aims to complement the undergraduate curriculum by
exposing the students to all stages of the design of a complex,
multi-objective design process. The course focuses on the process and
the student teams of 5 students form "companies" to undertake a
selected design project to produce an end product. The course is taught
by a team of 8 instructors ("design studio coordinators") and each team
works closely with one studio coordinator for the two terms. Open ended
projects aim for the students to generate creative and diverse
solutions for the projects they select. See the course site for details. EE493 Catalog Description, EE494 Catalog Description, Objectives.
Fall Term 2007-2008 (EE493) - Spring Term 2007-2008 (EE494)
Fall Term 2008-2009 (EE493) - Spring Term 2008-2009 (EE494)
Fall Term 2009-2010 (EE493) - Spring Term 2009-2010 (EE494)
Fall Term 2010-2011 (EE493) - Spring Term 2010-2011 (EE494)
Fall Term 2011-2012 (EE493) - Spring Term 2011-2012 (EE494)
Fall Term 2012-2013 (EE493) - Spring Term 2012-2013 (EE494) (Announced)
EE302 Feedback Systems
This course teaches the fundamentals of feedback systems and control
theory. It involves both classical control theory as well as modern
(state-space) control concepts. Topics include: Mathematical modeling:
Transfer functions, state equations, block diagrams. System response;
performance specifications. Stability of feedback systems:
Routh-Hurwitz criterion, principle of argument, Nyquist stability
criterion, gain margin and phase margin. Design of dynamic
compensators. Analysis and design techniques using root-locus.
State-space techniques: Controllability, observability, pole placement
and estimator design. Discrete-time control systems. Catalog Description. Course web site.
Spring Term 2005-2006
Spring Term 2006-2007
EE209
Fundementals of Electrical and Electronics Engineering
In this course, I try to introduce the non-EE engineering students
(e.g., Mechanical Engineering, Aeronotics Engineering, Chemical
Engineering) to the basic tools and techniques to deal with electricity
and electronics problems that they would encounter in their
professional career. I also they to stimulate the student about the
possibility of contributing to their chosen profession by making use of
some EE Eng knowledge.
In this course, I try to introduce the non-EE engineering students
(in particular Industrial Engineering students) to ideas about modeling
and analysing dynamic systems in engineering, industry and other
disciplines. Since concepts and methods of systems and control are such
powerful tools when applied to a variety of disciplines, I believe
motivated students would benefit from the content of this course. Among
topics discussed are methods of building mathematical models of
systems, Laplace transform methods, time and frequency domain
analysis , transfer function and state-space representation of of
dynamic systems as well as concepts of controllability, observability
and stability of systems.
