Ph.D., Middle East Technical University, Ankara, Grade: High Honours. Ph.D. in Electrical & Electronic Engineering, Control Theory

Reşat Özgür

Doruk

Curriculum Vitae

Personal

Education

2003–2008 Ph.D.,Middle East Technical University, Ankara,Grade: High Honours. Ph.D. in Electrical & Electronic Engineering, Control Theory

2000–2003 M.Sc.,Middle East Technical University, Ankara,Grade: High Honours. Master of Science in Electrical & Electronics Engineering, Control Theory 1996–2000 B.Sc.,Middle East Technical University, Ankara,Grade: High Honours.

Bachelor of Science in Mechanical Engineering

1989–1996 High School,TED Ankara College Foundation School, Ankara, . Secondary and High School Education

Master thesis

title MISSILE AUTOPILOT DESIGN BY PROJECTIVE CONTROL THEORY supervisors Dr. Erol Kocao¯glan, Professor

description In this thesis, autopilots are developed for missiles with moderate dynamics and stationary targets. Since the real missile model is non-linear, a linearisation process is required to get use of systematic linear controller design techniques. In the scope of this thesis, the linear quadratic full state feedback approach is applied for developing missile autopilots. However,the limitations of the measurement systems on the missiles restrict the availability of all states required for feedback. Because of this fact, the linear quadratic design will be approximated by the method of projective control theory. That enables the designer to use preferably static feedback or if necessary a controller plus a low order compensator combination to approximate the full state feedback reference. Autopilots are checked for the validity of linearisation, robust stability against aerodynamic, mechanical and measurement uncertainties.

Ph.D. thesis

title NONLINEAR CONTROLLER DESIGNS FOR A REACTION WHEEL ACTUATED OBSERVATORY SATELLITE

supervisors Dr. Erol Kocao¯glan, Professor

description Nonlinear attitude controllers are designed for a low earth orbit satellite intended to be used in observatory missions. As a difference from the classical satellite models existent in the literature, the model of this work incorporates the dynamics of the reaction wheel actuator. The main control approach of this research is developed by utilizing integrator back-stepping which provides a recursive stabilization methodology to the designer. For performance comparison, a second controller based on input output feedback linearisation (IOFL) is presented. Both of the approaches produce a torque demand law which is used for generating a desired reaction wheel velocity command. A reaction wheel controller uses the motor as an actuator and produces the necessary amount of the torque according to the desired wheel velocity level. In addition, a stability analysis against the external disturbance torques is provided for both control approaches.

Experience

Academic

10/2014– present

Doçent/Associate Professor, State Higher Education Comission/Interuniversity Board(YÖK-ÜAK), Ankara, TURKEY.

This is a higher level academic qualification awarded to the faculty members or researchers with a PhD, by the interuniversity board of Republic of Turkey (ÜAK) upon an assessment of publications and an oral examination. It is equivalent to the North American Associate Professorship.

2012–2014 Visiting Faculty,Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Mathematical modelling and system identification studies in theoretical neuroscience. Detailed Achievements:

{ Understanding the stimulus-response structure of the sensory neurons in general. { Advances in mathematical modelling of sensory neurons,

- Classification of models and their applicability to the sensory neuron modelling.

· Detailed realistic models (e.g: Hodgkin-Huxley, Ermentrout models).

· Static non-linear stimulus - response maps (e.g: feed-forward neural networks).

· Linear or piecewise linear models (e.g: leaky integrate and fire models).

· Dynamic recurrent structures and their generic nature (e.g.: recurrent neural net-works).

- System identification and optimal design of experiments,

· Importance of finding an optimal stimulus which is expected to decrease the estima-tion error covariance in the subsequent estimaestima-tion of the parameters of a general recurrent network structure.

· Concept of Fisher Information metric and its application in optimal design.

· The lack of continuous experimental data is an issue as there is no direct information on the variation of membrane potentials and associated firing rates. The only available information is the timing of the firing instants.

· Statistical evidence suggests that the firing instants obey the event timing distribution in an inhomogeneous Poisson process with time dependent neural firing rate as its rate parameter. This allows the derivation of a special likelihood function to perform a maximum likelihood estimation of the network parameters.

· The likelihood function should involve all the recordings of the neural firing informa-tion in order to reflect its statistics on the parameters adequately. However, this increases the computational complexity.

- Verification,

· Evaluation and comparison of the performances of a likelihood based estimation algorithm under randomly generated and optimally designed stimuli.

· Comparative evaluation helps the verification of the new methodology by proving its performance over a trivial method such as random stimuli based tests.

{ Computational challenges,

- Optimization algorithms: Selection of the most efficient methods and the right para-metric constraints.

- Numerical issues: Neurological limitations on the applicability of a single stimulus several times lead to a requirement of several different stimuli to be generated. This fact is another source of computational complexities.

- Speed concerns: The computational complexity of an application of optimal design to a dynamical model and that of the likelihood objective function used in the estimation procedures limit the algorithmic alternatives of optimization due to the speed and duration concerns.

- A local optimizer such as MATLABR _{fminconcan be invoked with multiple initial} guesses.

2008–2012 Lecturer, Middle East Technical University, Northern Cyprus Campus, Guzelyurt, KKTC, Mersin 10, TURKEY.

Taught courses on computer literacy, programming and information technologies. Conducted and coordinated electrical and electronic circuits laboratory courses.

Industrial Research

2001–2004 Research Engineering Specialist, Defense Research and Development Institute of the Turkish Scientific and Technological Research Institution, Mamak, Ankara, TURKEY.

Worked in research projects aiming at the design of linear and non-linear missile autopilot systems.

Languages

German Beginner’s Level Start-A2 Zertifikat des Goethe-Instituts

Computer skills

Programming: MATLAB and C Publishing: LateX (Intermadiate) and LyX General: MS Windows, Office and Visio Other: Various Hardware Related Advanced: Linux and related deployment

Interests & Leisure

Creative Home-brewing electronic circuits related to radio, simple power systems and com-puters

Leisure Walking and taking photographs of interesting places and events Music Listening to electronic music

References

Academic

{ Erol Kocao¯glan (Professor, Ph.D. Supervisor, Electrical and Electronic Engineer-ing Department, Middle East Technical University, Ankara, TURKEY, e-mail: [email protected])

{ Mübeccel Demirekler (Professor, Ph.D. & M.Sc. Examination Committee Chair, Electrical and Electronic Engineering Department, Middle East Technical Univer-sity, Ankara, TURKEY, e-mail: [email protected], [email protected])

{ Sadık Kakaç (Professor, Mechanical Engineering Department, T.O.B.B. Economy and Technology University, Ankara, TURKEY, e-mail: [email protected])

{ Kechen Zhang (Assist.Professor, Supervisor of Theoretical & Computational Neuroscience Laboratory of Biomedical Engineering Department, Baltimore, MD, USA, e-mail: [email protected])

Publications

R. Ö. Doruk and E. Kocao¯glan. A robustness analysis procedure for realistic missiles. Turk J Elec Engin, 13(2):241, 2005.

R. Ö. Doruk and E. Kocao¯glan. An almost disturbance decoupling solution of the attitude control problem. Aircraft Engineering and Aerospace Technology, 80(3):295–307, 2008.

R. Ö. Doruk and E. Kocao¯glan. Satellite attitude control by integrator back-stepping with internal stabilization. Aircraft Engineering and Aerospace Technology, 80(1):3– 10, 2008.

R. Ö. Doruk. Linearization-based attitude error regulation: multiplicative error case. Aircraft Engineering and Aerospace Technology, 81(6):536–540, 2009.

R. Ö. Doruk. Linearization in satellite attitude control with modified rodriguez parameters. Aircraft Engineering and Aerospace Technology, 81(3):199–203, 2009. R. Ö. Doruk. Feedback controlled electrical nerve stimulation: A computer simula-tion. Computer Methods and Programs in Biomedicine, 99(1):98–112, 2010. R. Ö. Doruk. Washout filter based control for hodgkin-huxley nerve cell dynamics. Turk J Elec Eng & Comp Sci. v18 i4, 2010.

R. Ö. Doruk. Development of a computer algorithm for feedback controlled electrical nerve fiber stimulation. Computer Methods and Programs in Biomedicine, 103(3):132–144, 2011.

R. Ö Doruk. Sdre based attitude control using modified rodriguez parameters. arXiv preprint arXiv:1103.5444, 2011.

R. Ö. Doruk. Control of repetitive firing in hodgkin–huxley nerve fibers using electric fields. Chaos, Solitons & Fractals, 52:66–72, 2013.

R. Ö. Doruk and Zhang K. Adaptive stimulus design for dynamic recurrent neural network models. Under preparation and will be submitted to Frontiers in Neural Circuits, 2014.