Global synchronization of general delayed complex networks with stochastic disturbances

In this paper, global synchronization of general delayed complex networks with stochastic disturbances, which is a zero-mean real scalar Wiener process, is investigated. The networks under consideration are continuous-time networks with time-varying delay. Based on the stochastic Lyapunov stability theory, Ito＇s differential rule and the linear matrix inequality （LMI） optimization technique, several delay-dependent synchronous criteria are established, which guarantee the asymptotical mean-square synchronization of drive networks and response networks with stochastic disturbances. The criteria are expressed in terms of LMI, which can be easily solved using the Matlab LMI Control Toolbox. Finally, two examples show the effectiveness and feasibility of the proposed synchronous conditions.

Finite-Time Synchronization of Fractional-Order Chaotic Systems with Different Structures under Stochastic Disturbances

This paper studies the finite-time synchronization of fractional-order chaotic systems with different structures under parameter disturbance and external disturbance. We put forward a fractional-order controller that can achieve the finite-time synchronization of any-order fractional-order chaotic systems under stochastic disturbances. This controller has good robustness and anti-interference performance. With the concept of the finite-time stability theory given, some judgment criterions for the synchronization of fractional-order chaotic systems are proved. This method can not only make the error systems have a faster convergence rate but also can be implemented in engineering easily. The numerical simulations of two specific examples demonstrate the effectiveness of the method. At the same time, the synchronised time of finite-time synchronization is shorter and faster than the complete synchronization and the time can be adjusted according to the parameters in the controller.

Adaptive robust control of nonholonomic systems with stochastic disturbances

This paper deals with nonholonomic systems in chained form with unknown covariance stochastic disturbances The objective is to design the almost global adaptive asymptotical controllers in probability Uo and u1 for the systems by using discontinuous control. A switching control law Uo is designed to almost globally asymptotically stabilize the state x0 in both the singular Xo（t0）=0 case and the non-singular Xo（to）≠O case. Then the state scaling technique is introduced for the discontinuous feedback into the （x1, x2,…, xn）-subsystem. Thereby, by using backstepping technique the global adaptive asymptotical control law u1 has been presented for （x1, x2, …, xn） -subsystem for both different Uo in non-singular x0 （t0）≠0 case and the singular case X0 （t0）=0. The control algorithm validity is proved by simulation.

Delay-Dependent H_∞ Synchronization for General Delayed Complex Networks with Stochastic Disturbances

In this paper, the H∞ synchronization is intensively investigated for general delayed complex dynamical networks. The network under consideration contains unknown but bounded nonlinear coupling functions, time-varying delay, external distur- bances, and lt6-type stochastic disturbances, which is a zero-mean real scalar Wiener process. Based on the stochastic Lyapunov stability theory, Ito＇s differential rule, and linear matrix inequality （LMI） optimization technique, some delay-dependent H∞ synchro- nization schemes are established, which guarantee robust stochas- tically mean square asymptotically synchronization for drive net- work and noise-perturbed response network as well as achieving a prescribed stochastic robust H∞ performance level. Finally, de- tailed and satisfactory numerical results have validated the feasi- bility and the correctness of the proposed techniques.

Discrete-time movement model of a group of trains on a rail line with stochastic disturbance

This paper presents a discrete-time model to describe the movements of a group of trains, in which some operational strategies, including traction operation, braking operation and impact of stochastic disturbance, are defined. To show the dynamic characteristics of train traffic flow with stochastic disturbance, some numerical experiments on a railway line are simulated. The computational results show that the discrete-time movement model can well describe the movements of trains on a rail line with the moving-block signalling system. Comparing with the results of no disturbance, it finds that the traffic capacity of the rail line will decrease with the influence of stochastic disturbance. Additionally, the delays incurred by stochastic disturbance can be propagated to the subsequent trains, and then prolong their traversing time on the rail line. It can provide auxiliary information for rescheduling trains When the stochastic disturbance occurs on the railway.

Distributed H2/H∞ Filter Design for Discrete-Time Switched Systems

This paper addresses an infinite horizon distributed H2/H∞ filtering for discrete-time systems under conditions of bounded power and white stochastic signals. The filter algorithm is designed by computing a pair of gains namely the estimator and the coupling. Herein, we implement a filter to estimate unknown parameters such that the closed-loop multi-sensor accomplishes the desired performances of the proposed H2 and H∞ schemes over a finite horizon. A switched strategy is implemented to switch between the states once the operation conditions have changed due to disturbances. It is shown that the stability of the overall filtering-error system with H2/H∞ performance can be established if a piecewise-quadratic Lyapunov function is properly constructed. A simulation example is given to show the effectiveness of the proposed approach.

Scheduling on 2-Machine Flow Shops Considering Disturbance on Job Processing Times

In this paper the scheduling problem to minimize the expected makespan is discussed on two-machine flow shops with random disturbance on job processing times. The problem is represented by a stochastic programming model. We approximate the stochastic problem by a deterministic problem which can be solved by Johnson's rule. The estimation of approximation error is also discussed by analyzing the stochastic model and its approximate LP model.

Design of satisfaction output feedback controls for stochastic nonlinear systems under quadratic tracking risk-sensitive index

In this paper, the design problem of satisfaction output feedback controls for stochastic nonlinear systems in strict feedback form under long-term tracking risk-sensitive index is investigated. The index function adopted here is of quadratic form usually encountered in practice, rather than of quartic one used to beg the essential difficulty on controller design and performance analysis of the closed-loop systems. For any given risk-sensitive parameter and desired index value, by using the integrator backstepping method, an output feedback control is constructively designed so that the closed-loop system is bounded in probability and the risk-sensitive index is upper bounded by the desired value.

Extended state observer for uncertain lower triangular nonlinear systems subject to stochastic disturbance

The extended state observer （ESO） is the most important part of an emerging control technology known as active disturbance rejection control to this day, aiming at estimating ＂total disturbance＂ from observable measured output. In this paper, we construct a nonlinear ESO for a class of uncertain lower triangular nonlinear systems with stochastic disturbance and show its convergence, where the total disturbance includes internal uncertain nonlinear part and external stochastic disturbance. The numerical experiments are carried out to illustrate effectiveness of the proposed approach.