Section: Research Program
Stabilization of interconnected systems

Linear systems: Analytic and algebraic approaches are considered for infinitedimensional linear systems studied within the inputoutput framework.
In the recent years, the YoulaKu$\stackrel{\u02c7}{\mathrm{c}}$era parametrization (which gives the set of all stabilizing controllers of a system in terms of its coprime factorizations) has been the cornerstone of the success of the ${H}_{\infty}$control since this parametrization allows one to rewrite the problem of finding the optimal stabilizing controllers for a certain norm such as ${H}_{\infty}$ or ${H}_{2}$ as affine, and thus, convex problem.
A central issue studied in the team is the computation of such factorizations for a given infinitedimensional linear system as well as establishing the links between stabilizability of a system for a certain norm and the existence of coprime factorizations for this system. These questions are fundamental for robust stabilization problems [1], [2].
We also consider simultaneous stabilization since it plays an important role in the study of reliable stabilization, i.e. in the design of controllers which stabilize a finite family of plants describing a system during normal operating conditions and various failed modes (e.g. loss of sensors or actuators, changes in operating points). Moreover, we investigate strongly stabilizable systems, namely systems which can be stabilized by stable controllers, since they have a good ability to track reference inputs and, in practice, engineers are reluctant to use unstable controllers especially when the system is stable.

In any physical systems a feedback control law has to account for limitation stemming from safety, physical or technological constraints. Therefore, any realistic control system analysis and design has to account for these limitations appearing mainly from sensors and actuators nonlinearities and from the regions of safe operation in the state space. This motivates the study of linear systems with more realistic, thus complex, models of actuators. These constraints appear as nonlinearities as saturation and quantization in the inputs of the system [10].
The project aims at developing robust stabilization theory and methods for important classes of nonlinear systems that ensure good controller performance under uncertainty and time delays. The main techniques include techniques called backstepping and forwarding, contructions of strict Lyapunov functions through socalled "strictification" approaches [4] and construction of LyapunovKrasovskii functionals [5], [6], [7] or or Lyapunov functionals for PDE systems [9].