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In this work, the problem of dissipative control is investigated for stochastic systems under the unreliable wireless network, in which there may exist stochastic fading channels. Firstly, a modified Rice fading model with disturbance-dependent noise is proposed. And then, a state-feedback controller with fading measurements is designed and the some sufficient conditions are derived such that the...
This paper presents an event-triggered sliding mode control (SMC) scheme for a class of uncertain stochastic systems over networks. System output is adequately sampled for further computation of a discrete-time event-trigger mechanism. Network-induced delays are described from event-trigger to controller. An event-driven zero-order-hold (ZOH) is employed to keep receiving and sending the delayed measurement...
This technical note is concerned with the stochastic state feedback H∞ control problem for continuous-time singular systems with state- and disturbance-dependent noise. A stochastic bounded real lemma for this class of systems is proved. Based on this result, the state feedback H∞ controller is designed, which ensures that the system not only is mean square admissible but also satisfies a prescribed...
This paper is concerned with a linear-quadratic (LQ) optimal control problem for the stochastic system with delay and Lévy processes. To solve this problem, we study the solvability of stochastic Hamiltonian system which is a fully coupled anticipated forward-backward stochastic differential equation with delay and Lévy processes (AFBSDDEL). By virtue of solvability of AFBSDDEL, we give a representation...
The paper has studied the problem of H∞ filtering for Markovian jump stochastic systems with uncertain transition probabilities. The systems under consideration not only involve uncertainties both in the system matrices and in the mode transition rate matrix, but also contain time-varying delays. By free-weighting matrix technique, a sufficient condition for the existence of an H∞ filter is developed...
This paper is concerned with the disturbance attenuation property of discrete-time stochastic systems with infinite Markov jump and multiplicative noises. Above all, the finite horizon H∞ performance is analyzed by means of a group of coupled difference Riccati equations, and a finite horizon bounded real lemma is obtained. Further, two versions of infinite horizon bounded real lemmas are presented...
This paper develops two proportional-type networked iterative learning control (NILC) schemes for a class of linear-time-invariant systems with stochastic packet dropout being subject to Bernoulli-type distribution. In the NILC schemes, we consider two types of compensation algorithms for dropped data: one of which is to replace the dropped data by that of the successfully captured at the concurrent...
This paper studies the consensus control problem of stochastic multi-agent systems subject to unknown state nonlinearities and external disturbances. A novel distributed integral-type sliding surface is constructed for each agent, and a sufficient condition based on linear matrix inequalities (LMIs) is given, which can guarantee the system states are mean-square consensus with H∞ disturbance attenuation...
In this paper, a class of stochastic systems described by the model of partial differential equations with random noise is investigated. The high order accurate compact finite difference numerical scheme is constructed to solve the system. The error analysis is given to illustrate the superiority of the numerical scheme. Then, the numerical simulation of the stochastic system is executed. The simulation...
This paper is concerned with the problem of global finite-time state feedback stabilization in probability for stochastic nonlinear systems under weaker conditions. A state feedback controller is recursively designed to rend the whole system globally finite-time stable in probability by stochastic stability theorem. Finally, a simulation example is included for illustrating the effectiveness of the...
In this paper, we propose a distributed stochastic model predictive control (DSMPC) algorithm for a team of linear subsystems sharing coupled probabilistic constraints. Each subsystem is subject to both parameter uncertainty and stochastic disturbances. To handle the probabilistic constraints, we first decompose the state trajectory into a nominal part and an uncertain part. The latter one is further...
This paper studies an optimal control problem derived by mean-field type forward-backward stochastic system, whose novel features are as follows: (i) Both the state equation and the cost functional are of mean-field type; (ii) The observation depends on the control; (iii) The drift coefficient of the observation equation is linear with respect to the state x. These features result in intrinsic difficulties...
To reduce the conservatism of asymptotic-stable function and input-state gain function of stochastic input-to-state stability, the notion of input-to-state stability in the mean squire (ISS-2M) is presented. By the aid of a comparison inequality, the analysis on criteria of ISS-2M is performed as neatly as that in the deterministic case.
This paper is concerned with the H∞ control problem for two-dimensional (2-D) stochastic systems with randomly occurring nonlinearity. The randomly occurring nonlinearity is modeled by using a Bernoulli random variable with known occurrence probability, which can characterize the phenomenon that the nonlinear disturbance may occur in a probabilistic way. Our attention is focused on the design of a...
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