Control Systems Engineering

Experience: 6 years

I have an experience in control systems engineering for aircrafts (UAVs) and testing devices for spacecraft power supply systems.


While studying in graduate school, I published several articles ( in English ) and three patents:

All of them are related to spacecraft power supply testing.


MATLAB is often the primary (and most mature) choice for the control systems development. Since at some point I started using pandas , I decided to move my control systems environment to Python as well and used python-control for this.

Today, I would work on control systems using Julia , because it has quite mature packages for control systems themselves, for uncertainty analysis , and it has a very impressive integrator collection .

Testing devices

I was involved in the development of electronic loads with power recovery and the development of programmable charging/discharging devices. I researched the issues of control systems coordination between individual load cells (that consisted of switched-mode converters and wide-band linear regulators) in order to obtain the required input admittance characteristics, in particular, for the possibility to induct current interference with an amplitude of tens of amperes.

In general, my work looked like this: first, simple control systems were made using IIR filters or broadband analog PID controllers for the initial mathematical models, then stable systems were identified (using the N4SID and MOESP algorithms), then MIMO H∞-controllers for several converters were synthesized and then mutual influence of the cells was balanced.

Rotorcraft UAV

For helicopters, I developed both the control system itself, DSP circuits and a mathematical simulation model of the helicopter, since helicopters are an unstable without closed control loops, which greatly complicates the synthesis of the control systems.

The mathematical model was largely based on the work of Padfield and Johnson and was developed in C++ (for more details see C++ section).

The control system was developed as a set of MIMO controllers due to the strong mutual influence of control loops (especially in swashplate cyclic pitch). In addition to the classical versions (H∞, PID), several experimental controllers were investigated, in particular:


Various digital filters have also been developed for control systems (see C++ ). In particular, when developing the module for determining the wind direction from indirect data, I built various types of estimators ( UKF , multiparticle ), but, in the end, the simple extended Kalman filter did a great job.


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