APPLICATIONS OF NONLINEAR MEASURE ABOUT l^2-NORM TO SYNCHRONIZATION ANALYSIS OF COMPLEX NETWORKS VIA THE GENERAL INTERMITTENT CONTROL

Based on the nonlinear measure about /-norm,a novel and effective approach is applied to estimate the scope of state vectors of dynamic systems.By the general intermittent control,some simple yet generic criteria are derived ensuring the exponential stability of dynamic systems.The numerical simulations,whose theoretical results are applied to robust synchronization of complex networks,demonstrate the effectiveness and feasibility of the proposed technique.

Real time remaining useful life prediction based on nonlinear Wiener based degradation processes with measurement errors

Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.

Active Disturbance Rejection Control for Uncertain Nonlinear Systems With Sporadic Measurements

This paper deals with the problem of active disturbance rejection control(ADRC)design for a class of uncertain nonlinear systems with sporadic measurements.A novel extended state observer(ESO)is designed in a cascade form consisting of a continuous time estimator,a continuous observation error predictor,and a reset compensator.The proposed ESO estimates not only the system state but also the total uncertainty,which may include the effects of the external perturbation,the parametric uncertainty,and the unknown nonlinear dynamics.Such a reset compensator,whose state is reset to zero whenever a new measurement arrives,is used to calibrate the predictor.Due to the cascade structure,the resulting error dynamics system is presented in a non-hybrid form,and accordingly,analyzed in a general sampled-data system framework.Based on the output of the ESO,a continuous ADRC law is then developed.The convergence of the resulting closed-loop system is proved under given conditions.Two numerical simulations demonstrate the effectiveness of the proposed control method.

INITIAL-OBLIQUE DERIVATIVE PROBLEMS FOR NONLINEAR PARABOLIC SYSTEMS WITH MEASURABLE COEFFICIENTS

This paper deals with some initial-oblique derivative boundary value problems for nonlinear nondivergent parabolic systems of several second order equations with measurable coefficients in multiply connected domains. Firstly, a priori estimates of solutions for the initial-boundary value problems are given, and then by using the above estimates of solutions and the Leray-Schauder theorem, the existence and uniqueness of solutions for the problems are proved.

Risk assessment model of tunnel water inrush based on improved attribute mathematical theory

Tunnel water inrush is one of the common geological disasters in the underground engineering construction.In order to effectively evaluate and control the occurrence of water inrush,the risk assessment model of tunnel water inrush was proposed based on improved attribute mathematical theory.The trigonometric functions were adopted to optimize the attribute mathematical theory,avoiding the influence of mutation points and linear variation zones in traditional linear measurement functions on the accuracy of the model.Based on comprehensive analysis of various factors,five parameters were selected as the evaluation indicators for the model,including tunnel head pressure,permeability coefficient of surrounding rock,crushing degree of surrounding rock,relative angle of joint plane and tunnel section size,under the principle of dimension rationality,independence,directness and quantification.The indicator classifications were determined.The links among measured data were analyzed in detail,and the objective weight of each indicator was determined by using similar weight method.Thereby the tunnel water inrush risk assessment model is established and applied in four target segments of two different tunnels in engineering.The evaluation results and the actual excavation data agree well,which indicates that the model is of high credibility and feasibility.

The chaotification of discrete Hopfield neural networks via impulsive control

The chaotification of discrete Hopfield neural networks is studied with impulsive control techniques. No matter whether the original systems are stable or not, chaotilication theorems for discrete Hopfield neural networks are derived, respectively. Finally, the effectiveness of the theoretical results is illustrated by some numerical examples.

Information Feedback Strategies in a Signal Controlled Network with Overlapped Routes

We investigate the effects of four different information feedback strategies on the dynamics of traffic, travelers＇ route choice and the resultant system performance in a signal controlled network with overlapped routes. Simulation results given by the cellular automaton model show that the system purpose-based mean velocity feedback strategy and the congestion coefficient feedback strategy have more advantages in improving network utilization efficiency and reducing travelers＇ travel times. The travel time feedback strategy and the individual purposed-based mean velocity feedback strategy behave slightly better to ensure user equity.

Efficient preparation of a four-photon cluster state with homodyne measurement via cross-Kerr nonlinearity

A scheme is proposed for generating a multiphoton entangled cluster state among four modes. The scheme only uses Kerr medium, beam splitter and homodyne measurements on coherent light fields, which can be efficiently made in quantum optical laboratories. The photon in the signal mode is prepared in a superposition state of the vacuum state and one-photon state while the probe beam is initially set in a coherent state superposition. The strong probe mode interacts successively with multiple signal-mode photons, each causing a conditional phase rotation in the probe mode. Subsequent momentum quadrature homodyne measurement of the probe mode will project the photons in the signal mode into the desired entangled states. It is shown that under certain conditions, the four-photon cluster state can be generated with high fidelity and high success probability, and the scheme is feasible by current experimental technology.

Chaos Control and Synchronization of Cellular Neural Network with Delays Based on OPNCL Control

The problem of chaos control and complete synchronization of cellular neural network with delays is studied. Based on the open plus nonlinear closed loop （OPNCL） method, the control scheme and synchronization scheme are designed. Both the schemes can achieve the chaos control and complete synchronization of chaotic neural network respectively, and their validity is further verified by numerical simulation experiments.

Applying nonlinear filtering in reverberation time measurement under strong background noise

Nonlinear filtering of impulse response obtained by M-sequence correlation method under strong background noise is presented. The research shows that the new method works very efficiently without the need to cut off impulse response data. Even if the ratio of signal to noise is below -15 dB, the same decay curve ranges can still be obtained as when S/N > 40 dB

Existence and Regularity of Solution for Strongly Nonlinear p（x）-Elliptic Equation with Measure Data

The first part of this paper is devoted to study the existence of solution for nonlinear p（x） elliptic problem A（u） =u in Ω, u = 0 on Ω, with a right-hand side measure, where Ω is a bounded open set of RN, N ≥ 2 and A （u） = -div（a （x, u, u）） is a Leray-Lions operator defined from W 0 1,p（x） （Ω） in to its dual W-1,p＇（x） （Ω）. However the second part concerns the existence solution, of the following setting nonlinear elliptic problems A（u）＋g（x,u, u） = u in Ω, u = 0 on Ω. We will give some regularity results for these solutions.

Nonlinearity for a parallel kinematic machine tool and its application to interpolation accuracy analysis

This paper is concerned with the kinematic nonlinearity measure of parallel kinematic machine tool (PKM), which depends upon differential geometry curvalure. The nonlinearity can be described by the curve of the solution locus and the equal interval input of joints mapping into inequable interval output of the end-effectors. Such curing and inequation can be measured by BW curvature. So the curvature can measure the nonlinearity of PKM indirectly. Then the distribution of BW curvature in the local area and the whole workspace are also discussed. An example of application to the interpolation accuracy analysis of PKM is given to illustrate the effectiveness of this approach.

A Survey of Repetitive Control for Nonlinear Systems

In aerospace engineering and industry, control tasks are often of a periodic nature,while repetitive control is especially suitable for tracking and rejection of periodic exogenous signals.Because of limited research effort on nonlinear systems, we give a survey of repetitive control for nonlinear systems in this paper.First,a brief introduction of repetitive control is presented.Then,after giving a brief overview of repetitive control for linear systems,this paper summarizes design methods and existing problems of repetitive control for nonlinear systems in detail.Lastly,relationships between repetitive control and other control schemes are analyzed to recognize repetitive control from different aspects more insightfully.