Attainability analysis in the stochastic sensitivity control

Abstract

For nonlinear dynamic stochastic control system, we construct a feedback regulator that stabilises an equilibrium and synthesises a required dispersion of random states around this equilibrium. Our approach is based on the stochastic sensitivity functions technique. We focus on the investigation of attainability sets for 2-D systems. A detailed parametric description of the attainability domains for various types of control inputs for stochastic Brusselator is presented. It is shown that the new regulator provides a low level of stochastic sensitivity and can suppress oscillations of large amplitude.

Keywords:

• nonlinear stochastic system
• feedback regulator
• attainability
• stochastic sensitivity

Additional information

Funding

This work was partially supported by RFBR [grant number 13-08-00069].