Improved derivative-dependent control of stochastic systems via delayed feedback implementation

Abstract

We study derivative-dependent control of the nth-order stochastic systems where derivatives are not available for measurements. The derivatives are approximated by finite differences giving rise to a delayed feedback. In the deterministic case, an efficient simple LMI-based method for designing of such static output-feedback and its sampled-data implementation was suggested recently. In the present paper, we extend this design to stochastic systems. We present two methods: the direct one that employs a stochastic extension of Lyapunov functionals used previously in the deterministic case, and the method which is based on neutral type model transformation and employs either augmented or simple Lyapunov functionals. Numerical examples illustrate the efficiency of the method.