Derivative-dependent control of stochastic systems via delayed feedback implementation

We study a delayed implementation of derivative dependent control for the third-order vector stochastic systems. The derivatives are approximated by finite differences giving rise to a delayed feedback. Recently, a new method for designing of such feedback under continuous-time and sampled measurements was suggested in the deterministic case. In the present paper, we extend this design to stochastic systems. For the case of continuous-time measurements, a neutral type model transformation and appropriate Lyapunov functionals are employed to derive linear matrix inequalities (LMIs). The results are further extended to the sampled-data implementation. Numerical examples illustrate the efficiency of the results.