Dynamic compensator design and H∞ admissibilization for delayed singular jump systems via Moore–Penrose generalized inversion technique

This paper is intended to study output feedback-based $H_{\infty }$ admissibilization for singular Markovian jump time-varying delays systems via Moore–Penrose generalized inversion technique. The main aim is to design singular dynamic compensator based on output feedback control idea and Moore–Penrose generalized inversion technique, such that the time-varying delays singular Markovian jump system realizes not only stochastic stability, but also regularity, impulse-freeness (which are collectively known as stochastic admissibility) and achieves $H_{\infty }$ interference level. Time delay-dependent and mode-dependent L–K candidate functional is constructed, Moore–Penrose generalized inversion technique is utilized, then the improved $H_{\infty }$ admissibilization conditions for singular Markovian jump time-varying delays systems are provided by virtue of linear matrix inequalities. Simulation examples including a direct current motor-controlled inverted pendulum system are employed to confirm the effectiveness and practicability of the addressed singular dynamic compensation technique.     

Hybrid-driven H∞ filter design for T–S fuzzy systems with quantization

This paper is mainly concerned with hybrid-driven $H_{\infty }$ filtering for a class of Takagi–Sugeno (T–S) fuzzy systems with quantization. To reduce the redundancy of transmission data and save the network bandwidth, a hybrid-driven scheme and a logarithmic quantizer are introduced in this paper. Firstly, by taking the effect of hybrid-driven scheme and quantization into consideration, a mathematical $H_{\infty }$ filter model for T–S fuzzy systems is constructed. Secondly, by applying Lyapunov stability theory, sufficient conditions for asymptotical stabilization of desired system are obtained. Moreover, an explicit algorithm for $H_{\infty }$ filter design is presented with the help of linear matrix inequality (LMI) techniques. Finally, numerical and physical simulations show the usefulness of the proposed filter design approach.     

The survival probability of critical and subcritical branching processes in finite state space Markovian environment

Let ${\left(Z_n\right)}_{n\ge 0}$ be a branching process in a random environment defined by a Markov chain ${\left(X_n\right)}_{n\ge 0}$ with values in a finite state space $\mathbb{X}$. Let ${\mathbb{P}}_i$ be the probability law generated by the trajectories of ${\left(X_n\right)}_{n\ge 0}$ starting at $X_0=i\in \mathbb{X}.$ We study the asymptotic behaviour of the joint survival probability ${\mathbb{P}}_i\left(Z_n>0,X_n=j\right)$, $j\in \mathbb{X}$ as $n\to +\infty$ in the critical and strongly, intermediate and weakly subcritical cases.     

Dilations of semigroups on von Neumann algebras and noncommutative Lp-spaces

We prove that any weak* continuous semigroup ${(T_t)}_{t?0}$ of factorizable Markov maps acting on a von Neumann algebra M equipped with a normal faithful state can be dilated by a group of Markov ?-automorphisms analogous to the case of a single factorizable Markov operator, which is an optimal result. We also give a version of this result for strongly continuous semigroups of operators acting on noncommutative ${\mathrm{L}}^p$-spaces and examples of semigroups to which the results of this paper can be applied. Our results imply the boundedness of the McIntosh's ${\mathrm{H}}^{\infty }$ functional calculus of the generators of these semigroups on the associated noncommutative ${\mathrm{L}}^p$-spaces generalising some previous work from Junge, Le Merdy and Xu. Finally, we also give concrete dilations for Poisson semigroups which are even new in the case of ${\mathbb{R}}^n$.     

Sharp non-asymptotic concentration inequalities for the approximation of the invariant distribution of a diffusion

Let ${\left(Y_t\right)}_{t\ge 0}$ be an ergodic diffusion with invariant distribution $\nu$. Consider the empirical measure ${\nu }_n≔{\left({\sum }_{k=1}^n{\gamma }_k\right)}^{-1}{\sum }_{k=1}^n{\gamma }_k{\delta }_{X_{k-1}}$ where ${\left(X_k\right)}_{k\ge 0}$ is an Euler scheme with decreasing steps ${\left({\gamma }_k\right)}_{k\ge 0}$ which approximates ${\left(Y_t\right)}_{t\ge 0}$. Given a test function $f$, we obtain sharp concentration inequalities for ${\nu }_n\left(f\right)-\nu \left(f\right)$ which improve the results in Honoré et al. (2019). Our hypotheses on the test function $f$ cover many real applications: either $f$ is supposed to be a coboundary of the infinitesimal generator of the diffusion, or $f$ is supposed to be Lipschitz.