State estimation of stochastic discrete-time linear systems subject to unknown inputs or constant biases has been widely studied but no work has been dedicated to the case where a disturbance switches between unknown input and constant bias. We show that such disturbance can affect a networked control system subject to deception attacks and data losses on the control signals transmitted by the ...

This article proposes an optimal method for approximate answer of stochastic Ito-Voltrra integral equations, via rationalized Haar functions and their stochastic operational matrix of integration. Stochastic Ito-voltreea integral equation is reduced to a system of linear equations. This scheme is applied for some examples. The results show the efficiency and accuracy of the method.

In this paper we study a class of optimal stochastic control problems involving two different time scales. The fast mode of the system is represented by deterministic state equations whereas the slow mode of the system corresponds to a jump disturbance process. Under a fundamental ”ergodicity” property for a class of ”infinitesimal control systems” associated with the fast mode, we show that th...

Stochastic self-assembly provides promising means for building micro-/nano-structures with a variety of properties and functionalities. Numerous studies have been conducted on the control and modeling of the process in engineered self-assembling systems constituted of modules with varied capabilities ranging from completely reactive nano-/micro-particles to intelligent miniaturized robots. Depe...

Recently, feedback control systems using random dither quantizers have been proposed for linear discrete-time systems. However, the constraints imposed on state and control variables have not yet been taken into account for the design of feedback control systems with random dither quantization. Model predictive control is a kind of optimal feedback control in which control performance over a fi...

Stochastic systems can be widely adopted for describing practical complex systems, such as meteorology. Recently, there have been many advances in the design of stochastic including system modeling, control, estimation, performance enhancement, and industrial applications. Motivated by these results, this Special Issue encourages researchers to publish their latest contributions study systems. ...

In this paper, the decentralized stabilization control approach based on the dynamic surface control (DSC) is proposed for a class of large-scale interconnected stochastic nonlinear systems. The proposed approach combined the existing dynamic surface control (DSC) with back-stepping technique. This approach can overcome the problem of “explosion of complexity” inherent in the back-stepping meth...