Finite-time gain-scheduled control on stochastic bioreactor systems with partially known transition jump rates

Abstract

In this paper, an observer-based finite-time continuous gain-scheduled control is designed for a class of stochastic bioreactor systems with partially known jump rates. By using gradient linearization approach, the nonlinear stochastic systems are described by a series of linear jump models at some selected working points, then based on stochastic Lyapunov-Krasovskii functional approach, a new robust stochastic finite-time stabilizable criterion is derived to ensure robust finite-time stabilization of the each jump linear system by means of linear matrix inequalities. This method is then extended to provide observer-based finite-time state feedback H infinity controllers for such linear jump systems. Lastly, continuous gain-scheduled approach is employed to design observer-based continuous H infinity controllers for the whole bioreactor jump systems. Simulation examples show the effectiveness and potential of the developed techniques.