Chaos Synchronization of Continuous Systems for Different Systems Parameters

Because parameter disturbed exist every practical system,so chaos synchronization for different system parameters is availabe. Chaos synchronization of continuous system for different system parameters is studied with the relation between chaotic synchronization and asymptotic stability, parameter adaptive and driving feedback. Lorenz system is used to verify the effectivenss of the proposed method,and the simulation results confirm it.     

Synchronization of Chaotic Systems Employing the Theory of Application of Linear Time-varying Impulsive Differential Equations

Employing the stability theory of linear non-autonomous impulsive differential equations, some sufficient conditions for the synchronization of unified chaotic systems and Lorenz chaotic systems are derived. This method can be applied to most of chaotic systems. The numerical simulations also demonstrate the efficiency of impulsive control.     

Exponential Stability Analysis for TS-model-based Fuzzy Chaotic Control Systems With Delays

The issue of exponential stability for TS-model-based fuzzy chaotic control systems with constant or time-varying delays is investigated. A linear-feedback fuzzy controller is designed using parallel dispersal compensation technique for a large class of chaotic control systems. By means of the Lyapunov-Krasovskii functional approach in combination of the linear matrix inequality and differential inequality techniques, the criteria for exponential stability of the TS-model-based fuzzy controller are derived, and the corresponding control laws are presented. The results are easy to be calculated numerically because of the linear matrix inequalities representation.     

Robust adaptive control for nonlinear chaotic systems

Tracking control of a nonlinear uncertain Chua's chaotic system is studied. With coordinate transform, Chua's chaotic system is transformed to a general form of a strict feedback control system. Combining the backstepping method with robust control technology, an adaptive parameter control law for a robust output feedback control scheme is developed for output tracking of nonlinear unknown systems. It is shown that the derived robust adaptive controller based on Lyapunov stability theory can guarantee global uniformly bounded ultimate property for all states of the closed loop system, and lead to tracking error decreasing at exponential speed. The simulation results show the effectiveness of the proposed approach.     

Chaotic Time Series Analysis Based on Radial Basis Function Networks

A method based on radial basis function networks for forecasting chaotic time series is proposed.The nonlinear time series identification problem is formulated with a nonlinear autoregressive moving average(NARMAX)model then a new identification algorithm based on dynamic radial basis function networks is proposed.Then this method is applied to the estimation of embedding dimension for chaotic time series of Henon mapping and the confirmation of the chaotic phenomena in stock markets of China,from which one can get the desired results.Further research directions are also pointed out.     

L2 Controller Design for Nonlinear Systems with Dead- Zone Modification

An adaptive robust L2design method with dead -zone modification is proposed for a class of nonlinear systems with external disturbances and uncertain parameters. With priori knowledge of the bounds of the parametric uncertainties, the smooth projection method and the dead zone modification technology are incorporated into the adaptive laws to prevent parameter drifting and reduce the computation burden. The number of parameter estimates is minimal for the adaptive system. The algorithm can guarantee the tracking errors asymptotically converge to the desired dead zone if the external disturbances are zero. The system satisfies L2 disturbance rejection criterion when the external disturbances are considered.     

Robust Adaptive Control Based on On-line Identification to Multi-parameters

In system controlled,Sampling these parameters and with parameters for controller in time, it is an object to adaptive control. The article presents a scheme that the structure parameters on it's model and model parameters is robust identified by on line, while to optimal of algorithm on adaptive control is fulfilled. In control scheme, method of intelligent identifying to the structure parameters(levels of model) and algorithm of robust pole placement are introduced also It is advancer for already mentioned scheme. Whole scheme presents new model on adaptive control.     

Adaptive Iterative Learning Control of Nonlinear Systems with Unknown Control Direction

An adaptive iterative learning control scheme is proposed for a class of mismatched nonlinear systems with periodic uncertainties and unknown control directions. The control algorithm has the following three features;the control method does not need control direction information; the periodic uncertainties are learned online by a learning control method; and the algorithm can deal with mismatched uncertainties. The proposed method can achieve asymptotical convergence along a learning repetition horizon. A simulation example is provided can demonstrate the effectiveness and feasibility of the control strategy.     

Image inpainting based on nonlinear anisotropic diffusions

Following the features of curvature and gradient at image edges,an image inpainting method based on nonlinear anisotropic diffusion is proposed.The diffusion can be conducted with different directions and different intensities according to the geometric features of the inpainted images.An adaptive factor is introduced based on the curvature and gradient of the image local geometric information,which can control the diffusion direction and diffusion intensity.At the edges in images,the diffusion coefficients are large for the horizontal directions,while the diffusion coefficients are small for the vertical directions.At the smooth regions,the diffusion coefficients are the same for different directions and they are usually large.Compared with the typical total variation method,the curvature derivation diffusion method,and P-laplace constant variation method,the experimental results show that the proposed method can improve the qualities of the inpainted images     

public-key Encryption Based on Torus Automorphisms

Chaotic maps with its characteristic are very useful in cryptography, however, compared with wide application in symmetric system, the research about chaos in public-key encryption system is still few. Through analysing the period of toms automorphisms which is a prototype of chaotic map, and making use of the framework of the traditional public-key algorithm RSA, the authors propose a chaotic public-key encryption algorithm based on toms automorphisms. Its security is based on the intractability of the integer factorization problem as RSA, and it is able to resist the chosen-ciphertext attack against RSA and easy to be implemented.     

The frequency detection model with anti-noise in the autonomous chaotic system

A method of detecting the signal frequency which is disturbed by the noise based on the autonomous chaotic system is proposed. A signal with noise was added to an autonomous chaotic system, and then a negative feedback was imposed to it. The feedback gain was appropriately adjusted, so as to let the noisy system orbit be a limit cycle. The number of times that the orbit went directly through a plane was calculated by loop phase technology, and the vibration frequency was found according to it. The frequency of system is determined by the frequency of the test signal, yet free from noise, so the frequency of the test signal is the vibration frequency of the system. Simulation results further demonstrate the effectiveness of the method.     

基于混沌时间序列的马尾松角胫象林间诱捕数量短期预测

为了对马尾松角胫象的防治及松材线虫病的控制提供技术支持,利用混沌时间序列的基本原理,分析马尾松角胫象林间诱捕序列,并重构其相空间及计算最大Lyapunov指数。结果表明：马尾松角胫象林间诱捕序列具有混沌特性。在此基础上,应用加权一阶局域预测模型对马尾松角胫象种群动态进行短期预测,结果显示在最长可预报时间尺度内该模型的预测成功率为100%。     

A Review of Recent Advances in Research and Development on Vehicle Semi-Active Suspension Systems

Based on the systems engineering theory, this paper reviews the trend of researches and developments on vehicle semiactive suspension systems, analyzes states of researches on electrorheological fluids and magnetorheological fluids material,and puts forward semi_active suspension sytems based on magnetorheological fluids damper. On the basis of summing up existing methods for vibration control on semi_active suspension systems, emphases are put on the discussion of aplication of PID control. linear optimal control,adaptive control and intelligent control on the semi_active suspension systems. The compound control strategy is put forward based on the skyhook damping control theory, fuzzy control theory and adaptive control theory. Moreover, the integral idea about the research and development of semi_active suspension is based on MR damper,and discusses some theories and applied problems deserving research.     

基于PID算法对热风炉热风温度控制及仿真分析

在农作物金银花干燥期间,为了满足干燥热风的温度和风速的稳定性要求,针对热风炉出风口热风温度与设定的温度值滞后和稳定性差等问题,设计了一套以单片机STM32作为核心处理器和模糊自适PID算法作为参数控制器的控制系统,实现模糊自适PID算法对参数进行调整。利用Matlab语言建立模型,对整套控制系统进行仿真分析。结果表明:出风口热风温度的稳定性能达到95%以上,该研究方法提高控制系统的性能,有利于农作物干燥的质量和效率。     

Image Secure Communication Based on Logistic Map

The chaotic sequences generated by logistic map are used as the carrier, and the image secure communication scheme is proposed based on that the sequences possess a good correlation property. Promising results are obtained on Lenna image by computer simulation. The obtained results indicate that the transmitted source image can be correctly recovered and the proposed scheme is reliable when transmitter and receiver using identical initial value even under the situations of a noisy channel. However, the tiny difference of initial value between transmitter and receiver will result in failure to communication. Finally, the quality of recovered source image is assessed, and the approximate formula of bit-error rate in term of code length is also obtained.     

THE AIGORITHM OF COMPUTED TORQUE -SELF TUNING CONTROL FOR ROBOT

Some control schemes for complex nonlinear systems have been developed recently and the robotic adaptive control is one of the typical examples. Due to the inevitable presence of unmodeled dynamics,if the adaptive control technique combined with nonlinear model-based control takes full advantages over any known parametric model while dealing with the remaining unknown parameters by using adaptive control,it may be an efficient control strategy, therefore.an algorithm of computed torque-self tuning control for robot is presented, whose simulation results have proved its effectiveness.     

Rate control using the rate-distortion properties of the foreground and background regions

In order to improve the rate control performance of video encoder, video frames are segmented into two regions according to the video content, i.e. the foreground region containing the main moving objects and the background region containing the relatively static scene. The rate-distortion properties of the two regions are analyzed. Based on the analyses, a novel region-based macroblock layer rate control method for H.264/AVC is proposed. For the bit allocation process, more target bits can be assigned to the important macroblocks by employing an adaptive factor determined by the region information. Then, the quantization parameter (QP) is computed by using the quadratic model with different parameters related to the two regions. The computed QP is further adjusted to suppress the coding quality fluctuation between the two regions, as well as the quality fluctuation among the consecutive macroblocks. Finally, the rate control parameters are updated after coding the current macroblock. Experimental results demonstrate the mismatches between the actual coding bit-rates and the target bit-rates are reduced, while the coding performance of the encoder and the subjective visual quality of the reconstructed video are improved.     

Fuzzy adaptive tracking control for MIMO nonlinear time-varying delay systems

A fuzzy adaptive tracking control scheme is proposed for MIMO nonlinear time-varying delay systems. A fuzzy T-S model-based adaptive time-varying delay fuzzy logic systems is developed to approximate the unknown nonlinear time-varying delay functions.Thus, the modeling to nonlinear systems is implemented. The update laws for parameters of the fuzzy logic systems are derived by the tracking error. A Hcompensator is designed to eliminate fuzzy approximation errors and external disturbances. Based on Lyapunov stability theorem, the proposed control scheme can guarantee the stability of the closed loop systems and obtain anticipant Htracking performance as well. Simulation results of the manipulator demonstrate the effectiveness of the control scheme.