This paper studies the static output-feedback (SOF) stabilization problem for discrete-time Markovian jump systems from a novel perspective. The closed-loop system is represented in a system augmentation form, in which input and gain-output matrices are separated. By virtue of the system augmentation, a novel necessary and sufficient condition for the existence of desired controllers is establi...

We consider the stability properties and stabilizing problem of sampled-data networked controlled linear systems with Markovian packet losses. A binary Markov chain is used to characterize the packet loss phenomenon of the network. Then with the Markovian packet loss assumption, we obtain a discrete-time augmented Markov jump linear system which describes the continuous-time linear system evolv...

The hybrid joints of manipulators can be switched to either active actuated or passive underactuated mode as needed. Consider the property of hybrid joints, the system switches stochastically between active and passive systems, and the dynamics of the jump system cannot stay on each trajectory errors region of subsystems forever; therefore, it is difficult to determine whether the closed-loop s...

This paper describes the synthesis of robust output feedback H1 control for a class of uncertain Markovian jump linear systems with time-delays which are time-varying and depend on the system modes of operation. Under the assumption of known bounds of system uncertainties and the control system gain variations, we present sufficient conditions on the existence of robust stochastic stability and...

Some invariance principles for additive functionals of simple exclusion with finite-range translation-invariant jump rates p i j = p j − i in dimensions d ≥ 1 are established. A previous investigation concentrated on the case of p symmetric. The principal tools to take care of nonreversibility, when p is asymmetric, are invariance principles for associated random variables and a “local balance”...

A problem of robust guaranteed cost control of stochastic discrete-time systems with parametric uncertainties under Markovian switching is considered. The jump Markovian switching is modelled by a discrete-time Markov chain and the noise or stochastic environmental disturbance is modelled by a sequence of identically independently normally distributed random variables. Using linear matrix inequ...

We consider a class of stochastic dynamical systems, called piecewise deterministic Markov processes, with states (x, σ) ∈ Ω × Γ, Ω being a region in R or the d–dimensional torus, Γ being a finite set. The continuous variable x follows a piecewise deterministic dynamics, the discrete variable σ evolves by a stochastic jump dynamics and the two resulting evolutions are fully–coupled. We study st...

In this paper we present an iterative technique based on Monte Carlo simulations for deriving the optimal control of the infinite horizon linear regulator problem of discretetime Markovian jump linear systems for the case in which the transition probability matrix of the Markov chain is not known. It is well known that the optimal control of this problem is given in terms of the maximal solutio...

In this article, the Input-to-state stability theory is used to investigate stochastic Cohen–Grossberg bidirectional associative memory neural network with time-varying delay. addition, Markovian jump parameters are considered in model determine continuous-time, discrete-state Markov chain. By utilizing Lyapunov functional and weak infinitesimal generator algebraic conditions derived for criter...

The stability and performance of a networked control system (NCS) strongly depends on the transmission delay. However, the randomness of the transmission delay is an intrinsic property in the network communication, e.g. Ethernet. Aiming at NCS with random transmission delay, a novel control approach is proposed. The transmission delays from sensorto-controller (SC) and controller-to-actuator (C...