Finite-time Control For Several Classes Of Discrete-time Systems With Norm Bounded Disturbances

In this paper,the finite-time stability issue is investigated for discrete-time Markov jumping neural networks with bounded disturbances and time-varying delays,stochastic Markov jumping systems with output feedback,discrete-time switching systems with time-delay and Markov jumping nonlinear systems with unknown information.The main work of this paper is as follows:1)The problem of finite-time H_? filtering for discrete Markov jump neural network systems with norm-bounded disturbances and time-varying delays is studied.The H_? state estimation of extended neural network systems is designed to guarantee the stochastic finite-time boundedness of error dynamics with a given disturbance attenuation level in a finite time interval.A sufficient condition for the solvability of the state estimation problem is given by using the Koff system method.2)The problem of robust finite time H_? control for stochastic jump systems with delay and output feedback is addressed.A stochastic finite-time H_? output feedback controller is derived.Sufficient conditions for stochastic finite-time H_? stability are obtained by translating them into linear matrix inequalities with fixed parameters.3)The filtering issue of discrete switched systems with time-varying delays is presented.By using bounded real lemma and linear matrix inequality,sufficient criteria are obtained for H_? finite-time boundedness and a filter is designed.4)The problem of finite-time H_? bounded control is studied for a class of uncertain Markovian jumping nonlinear systems.The purpose of this section is to derive a stochastic finite-time controller so that the resulting uncertain stochastic nonlinear model is stochastic finite-time H_? bounded.The stochastic analysis technique and free weighted matrix method are applied to constrain the problem.The stochastic finite-time H_? boundedness criteria are provided for the class of uncertain stochastic nonlinear dynamical systems...