
Home
Laboratory of Adaptive and Robust Control Systems of Institute of Control Sciences RAS
was founded by Academician Ya. Z. Tsypkin in 1956. By that time, main research
interests lied in the theory of relay, impulse, and digital automatic control.
Since midsixties, efforts were shifted to adaptive systems, and this
area is still of interest in the lab. Later, in 70s and 80s, most efforts were
concentrated on the design of robust and optimal algorithms in adaptive control
and identification. Such algorithms possess high rate of convergence, and
available information about the system can be exploited in full.
During the last decade, the following three research directions are worth
emphasizing.
The first one deals with robust control theory. Within the classical approach,
the theory is developed under assumptions that our knowledge about the system
is precise. However, in reallife applications, the presence of various
uncertainties is unavoidable, and the system description is only known to a
certain accuracy. Robust control theory is aimed at accounting for such
uncertainties and offers effective tools for analysis and design of control
systems which are "insensitive", or robust, against this imprecise description.
At present, this research area is considered highly important in the control
community.
The second, newly developed research activity is directed to fixedorder
controller design. All modern approaches to optimal control (such as
H^{∞}  theory,
µ  synthesis, LMI  based design,
l_{1}  optimization) quite often yield regulators of
very high orders, which even exceed the order of the plant. Hence, various
modifications of the existing techniques are desired, leading to loworder
controller design.
The third line of research lies in a more classical framework of identification
and adaptive control. Here, two topics are of most interest. The first one
relates to the information approach to adaptive control of stochastic systems.
Within this approach, it is possible to determine limiting (optimal) rates of
convergence for the methods, and algorithms can be advised which implement
this optimal behavior under various assumptions on the uncertainty.
The second subdirection, the socalled frequency theory of identification
and adaptive control, is developed under assumption that exogenous disturbances
are unknownbutbounded. The basis for this research is identification of
systems using harmonic test inputs followed by controller design with the
methods of optimal control theory.
