Intelligent modeling and control for nonlinear systems with rate-dependent hysteresis

A new modeling approach for nonlinear systems with rate-dependent hysteresis is proposed. The approach is used for the modeling of the giant magnetostrictive actuator, which has the rate-dependent nonlinear property. The models built are simpler than the existed approaches. Compared with the experiment result, the model built can well describe the hysteresis nonlinear of the actuator for input signals with complex frequency. An adaptive direct inverse control approach is proposed based on the fuzzy tree model and inverse learning and special learning that are used in neural network broadly. In this approach, the inverse model of the plant is identified to be the initial controller firstly. Then, the inverse model is connected with the plant in series and the linear parameters of the controller are adjusted using the least mean square algorithm by on-line manner. The direct inverse control approach based on the fuzzy tree model is applied on the tracing control of the actuator by simulation. The simulation results show the correctness of the approach. Supported by the National Natural Science Foundation of China (Grant No. 60534020), the National Basic Research Program of China (Grant No. G2002cb312205-04), the Research Fund for the Doctoral Program of Higher Education (Grant No. 20070006060), and the Key Subject Foundation of Beijing (Grant Nos. XK100060526, XK100060422)     

Steady-state performance analysis of HOS-based blind adaptive multiuser detection

The blind adaptive multiuser detections based on higher-order statistics (HOS) can obtain higher steady-state decorrelating performance than the conventional linear algorithm under the high SNR condition. However, the closed-form analysis for this steady-state performance is scarce due to the complication of analyzing the nonlinear updates of the adaptive algorithm. An analysis approach based on ordinary differential equation (ODE) method is proposed to get the closed-form excess mean-square error (EMSE) expression of the HOS-based multiuser detections. The simulation and the comparison verify the results of the analysis. Supported by the National Natural Science Foundation of China (Grant No. 60432040), and the Guangxi Natural Science Foundation (Grant Nos. 0731026, 0731025)     

Min-max model predictive control for constrained nonlinear systems via multiple LPV embeddings

A min-max model predictive control strategy is proposed for a class of constrained nonlinear system whose trajectories can be embedded within those of a bank of linear parameter varying (LPV) models. The embedding LPV models can yield much better approximation of the nonlinear system dynamics than a single LTV model. For each LPV model, a parameter-dependent Lyapunov function is introduced to obtain poly-quadratically stable control law and to guarantee the feasibility and stability of the original nonlinear system. This approach can greatly reduce computational burden in traditional nonlinear predictive control strategy. Finally a simulation example illustrating the strategy is presented. Supported by the National Natural Science Foundation of China (Grant Nos. 60774015, 60825302, 60674018), the National High-Tech Research & Development Program of China (Grant No. 2007AA041403), the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20060248001), and partly by Shanghai Natural Science Foundation (Grant No. 07JC14016)     

A novel algorithm for explicit optimal multi-degree reduction of triangular surfaces

This paper introduces the algebraic property of bivariate orthonormal Jacobi polynomials into geometric approximation. Based on the latest results on the transformation formulae between bivariate Bernstein polynomials and Jacobi polynomials, we naturally deduce a novel algorithm for multi-degree reduction of triangular B~zier surfaces. This algorithm possesses four characteristics： ability of error forecast, explicit expression, less time consumption, and best precision. That is, firstly, whether there exists a multi-degree reduced surface within a prescribed tolerance is judged beforehand; secondly, all the operations of multi-degree reduction are just to multiply the column vector generated by sorting the series of the control points of the original surface in lexicographic order by a matrix; thirdly, this matrix can be computed at one time and stored in an array before processing degree reduction; fourthly, the multi-degree reduced surface achieves an optimal approximation in the norm L2. Some numerical experiments are presented to validate the effectiveness of this algorithm, and to show that the algorithm is applicable to information processing of products in CAD system.     

Analysis and side peaks identification of Chinese DTTB signal ambiguity functions for passive radar

Passive radar is one of the current research focuses. The implementation of the Chinese standard digital television terrestrial broadcasting (DTTB) creates a new opportunity for passive radar. DTTB system contains single-carrier and multicarrier application modes. In this paper, ambiguity functions of the DTTB signals in the single-carrier and multicarrier application modes are analyzed. Ambiguity function of the DTTB signal contains one main peak and many side peaks. The relative positions and amplitudes of the side peaks are derived and the reasons for the occurrence of the side peaks are obtained. The side peaks identification (SPI) algorithm is proposed for avoiding the false alarms caused by the side peaks. Experimental results show that the SPI algorithm can indentify all the side peaks without the power loss. This research provides the foundation for designing the DTTB based passive radar. Supported by the National Natural Science Foundation of China (Grant No. 60232010), the Ministerial Foundation of China (Grant No. A2220060039) and the National Natural Science Foundation of China for Distinguished Young Scholars (Grant No. 60625104)     

A novel strong tracking finite-difference extended Kalman filter for nonlinear eye tracking

Non-intrusive methods for eye tracking are important for many applications of vision-based human computer interaction. However, due to the high nonlinearity of eye motion, how to ensure the robustness of external interference and accuracy of eye tracking poses the primary obstacle to the integration of eye movements into todays’s interfaces. In this paper, we present a strong tracking finite-difference extended Kalman filter algorithm, aiming to overcome the difficulty in modeling nonlinear eye tracking. In filtering calculation, strong tracking factor is introduced to modify a priori covariance matrix and improve the accuracy of the filter. The filter uses finite-difference method to calculate partial derivatives of nonlinear functions for eye tracking. The latest experimental results show the validity of our method for eye tracking under realistic conditions. Supported by the National Natural Science Foundation of China (Grant No. 60572027), the Outstanding Young Researchers Foundation of Sichuan Province (Grant No. 03ZQ026-033), the Program for New Century Excellent Talents in University of China (Grant No. NCET-05-0794), and the Young Teacher Foundation of Mechanical School (Grant No. MYF0806)     

A moving object segmentation algorithm for static camera via active contours and GMM

Moving object segmentation is one of the most challenging issues in computer vision. In this paper, we propose a new algorithm for static camera foreground segmentation. It combines Gaussian mixture model (GMM) and active contours method, and produces much better results than conventional background subtraction methods. It formulates foreground segmentation as an energy minimization problem and minimizes the energy function using curve evolution method. Our algorithm integrates the GMM background model, shadow elimination term and curve evolution edge stopping term into energy function. It achieves more accurate segmentation than existing methods of the same type. Promising results on real images demonstrate the potential of the presented method. Supported by National Basic Research Program of China (Grant No. 2006CB303105), the Chinese Ministry of Education Innovation Team Fund Project (Grant No. IRT0707), the National Natural Science Foundation of China (Grant Nos. 60673109 and 60801053), Beijing Excellent Doctoral Thesis Program (Grant No. YB20081000401), Beijing Municipal Natural Science Foundation (Grant No. 4082025), and Doctoral Foundation of China (Grant No. 20070004037)     

Demand-Driven Memory Leak Detection Based on Flow- and Context-Sensitive Pointer Analysis

We present a demand-driven approach to memory leak detection algorithm based on flow- and context-sensitive pointer analysis. The detection algorithm firstly assumes the presence of a memory leak at some program point and then runs a backward analysis to see if this assumption can be disproved. Our algorithm computes the memory abstraction of programs based on points-to graph resulting from flow- and context-sensitive pointer analysis. We have implemented the algorithm in the SUIF2 compiler infrastructure and used the implementation to analyze a set of C benchmark programs. The experimental results show that the approach has better precision with satisfied scalability as expected. This work is supported by the National Natural Science Foundation of China under Grant Nos. 60725206, 60673118, and 90612009, the National High-Tech Research and Development 863 Program of China under Grant No. 2006AA01Z429, the National Basic Research 973 Program of China under Grant No. 2005CB321802, the Program for New Century Excellent Talents in University under Grant No. NCET-04-0996, and the Hunan Natural Science Foundation under Grant No. 07JJ1011.     

Realizations of BELS as WIV method in both direct and indirect closed-loop system identification

The bias eliminated least squares (BELS) method, which is known as efficient for unknown parameter estimation of transfer function in the correlated noise case, has been developed and applied effectively to the closed-loop system identification. In this paper, under the general settings, the realizations of the BELS method as a weighted instrumental variables (WIV) method in both direct and indirect closed-loop system identification are established through constructing an appropriate weighting matrix in the WIV method. The constructed structures are similar in both cases, which reveals that all the proof procedures of the two realizations are the same. Thus, the unified realizations of the BELS as the WIV method for the closed-loop system identification can be built. A simulation example is given to validate our theoretical analysis. Supported by the National Natural Science Foundation of China for Distinguished Young Scholars (Grant No. 60625104), the Ministerial Foundation of China (Grant No. A2220060039), and the Fundamental Research Foundation of BIT (Grant No. 1010050320810)     

Globally exponentially attractive sets of the family of Lorenz systems

In this paper, the concept of globally exponentially attractive set is proposed and used to consider the ultimate bounds of the family of Lorenz systems with varying parameters. Explicit estimations of the ultimate bounds are derived. The results presented in this paper contain all the existing results as special cases. In particular, the critical cases, b→ 1^＋ and a→0^＋, for which the previous methods failed, have been solved using a unified formula.     

随机系统的多模型直接自适应解耦控制器

针对多变量离散时间随机系统, 提出了一种采用广义最小方差性能指标的多模型直接自适应解耦控制器. 该多模型控制器由多个固定控制器和两个自适应控制器构成. 固定控制器用以覆盖系统参数的可能变化范围, 自适应控制器用以保证系统的稳定性和提高暂态性能. 该多模型控制器利用矩阵的伪交换性和拟Diophantine方程性质, 基于广义最小方差性能指标, 将随机系统辨识算法和最优控制器设计相结合, 直接辨识出控制器的参数, 通过广义最小方差性能指标中加权多项式的选取,不但实现了多变量系统的动态解耦控制, 而且消除了稳态误差、配置了闭环极点. 文末给出了全局收敛性分析. 仿真结果表明该方法明显优于常规自适应控制器.     

Power allocation for non-orthogonal decode-and-forward cooperation protocol

This paper studies the power allocation problem for the non-orthogonal decode-and-forward (NDF) cooperation protocol with selection relaying. With the availability of the magnitudes of all channel gains at the source, the power allocation is explored that maximizes the mutual information between the source and destination subject to a total power constraint. The minimum power that avoids the outage of the relay is set as a condition, under which the power allocation problem becomes one of selecting the optimal one from several allocation factor triplets. It is shown that the power allocation scheme can provide considerable performance gain, and the non-orthogonal cooperation protocol is superior to the orthogonal protocol and direct transmission. Supported by the Project of Natural Science Foundation of Jiangsu Province (Grant No. BK2006701), the National Natural Science Foundation of China (Grant No. 60672079), and the National High-Tech Research & Development Program of China (Grant No. 2007AA01Z267)     

Adaptive blind separation of underdetermined mixtures based on sparse component analysis

The independence priori is very often used in the conventional blind source separation （BSS）. Naturally, independent component analysis （ICA） is also employed to perform BSS very often. However, ICA is difficult to use in some challenging cases, such as underdetermined BSS or blind separation of dependent sources. Recently, sparse component analysis （SCA） has attained much attention because it is theoretically available for underdetermined BSS and even for blind dependent source separation sometimes. However, SCA has not been developed very sufficiently. Up to now, there are only few existing algorithms and they are also not perfect as well in practice. For example, although Lewicki-Sejnowski＇s natural gradient for SCA is superior to K-mean clustering, it is just an approximation without rigorously theoretical basis. To overcome these problems, a new natural gradient formula is proposed in this paper. This formula is derived directly from the cost function of SCA through matrix theory. Mathematically, it is more rigorous. In addition, a new and robust adaptive BSS algorithm is developed based on the new natural gradient. Simulations illustrate that this natural gradient formula is more robust and reliable than Lewicki-Sejnowski＇s gradient.     

Pores-Preserving Face Cleaning Based on Improved Empirical Mode Decomposition

In this paper,we propose a novel method of cleaning up facial imperfections such as bumps and blemishes that may detract from a pleasing digital portrait.Contrasting with traditional methods which tend to blur facial details, our method fully retains fine scale skin textures(pores etc.) of the subject.Our key idea is to find a quantity,namely normalized local energy,to capture different characteristics of fine scale details and distractions,based on empirical mode decomposition,and then build a quantitat...     

An improved control algorithm for high-order nonlinear systems with unmodelled dynamics

In this paper, we consider a class of high-order nonlinear systems with unmodelled dynamics from the viewpoint of maintaining the desired control performance （e,g., asymptotical stability） and reducing the control effort. By introducing a new reseating transformation, adopting an effective reduced-order observer, and choosing an ingenious Lyapunov function and appropriate design parameters, this paper designs all improved output-feedback controller. The output-feedback controller guarantees the globally asymptotieal stability of the closed-loop system. Subsequently, taking a concrete system for an example, the smaller critical values for gain parameter and resealing transformation parameter are obtained to effectively reduce the control effort.     

Randomized competitive algorithms for the list update problem

We prove upper and lower bounds on the competitiveness of randomized algorithms for the list update problem of Sleator and Tarjan. We give a simple and elegant randomized algorithm that is more competitive than the best previous randomized algorithm due to Irani. Our algorithm uses randomness only during an initialization phase, and from then on runs completely deterministically. It is the first randomized competitive algorithm with this property to beat the deterministic lower bound. We generalize our approach to a model in which access costs are fixed but update costs are scaled by an arbitrary constantd. We prove lower bounds for deterministic list update algorithms and for randomized algorithms against oblivious and adaptive on-line adversaries. In particular, we show that for this problem adaptive on-line and adaptive off-line adversaries are equally powerful.A preliminary version of these results appeared in a joint paper with S. Irani in theProceedings of the 2nd Symposium on Discrete Algorithms, 1991 [17].This research was partially supported by NSF Grants CCR-8808949 and CCR-8958528.This research was partially supported by NSF Grant CCR-9009753.This research was supported in part by the National Science Foundation under Grant CCR-8658139, by DIMACS, a National Science Foundation Science and Technology center, Grant No. NSF-STC88-09648.     

New delay-dependent criterion for the stability of recurrent neural networks with time-varying delay

This paper is concerned with the global asymptotic stability of a class of recurrent neural networks with interval time-varying delay. By constructing a suitable Lyapunov functional, a new criterion is established to ensure the global asymptotic stability of the concerned neural networks, which can be expressed in the form of linear matrix inequality and independent of the size of derivative of time varying delay. Two numerical examples show the effectiveness of the obtained results. Supported by the National Natural Science Foundation of China (Grant Nos. 60534010, 60728307, 60774048, 60774093), the Program for Cheung Kong Scholars and Innovative Research Groups of China (Grant No. 60521003) and the National High-Tech Research & Development Program of China (Grant No. 2006AA04Z183), China Postdoctoral Sciencer Foundation (Grant No. 20080431150), and the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 200801451096)     

Multi-spectral image fusion method based on two channels non-separable wavelets

A construction method of two channels non-separable wavelets filter bank which dilation matrix is [1, 1; 1,-1] and its application in the fusion of multi-spectral image are presented. Many 4×4 filter banks are designed. The multi-spectral image fusion algorithm based on this kind of wavelet is proposed. Using this filter bank, multi-resolution wavelet decomposition of the intensity of multi-spectral image and panchromatic image is performed, and the two low-frequency components of the intensity and the panchromatic image are merged by using a tradeoff parameter. The experiment results show that this method is good in the preservation of spectral quality and high spatial resolution information. Its performance in preserving spectral quality and high spatial information is better than the fusion method based on DWFT and IHS. When the parameter t is closed to 1, the fused image can obtain rich spectral information from the original MS image. The amount of computation reduced to only half of the fusion method based on four channels wavelet transform.     

Iterative identification and control design with optimal excitation signals based on <Emphasis Type="Italic">υ</Emphasis>-gap

An iterative identification and control design method based on υ-gap is given to ensure the stability of closed-loop system and control performance improvement. The whole iterative procedure includes three parts: the optimal excitation signals design, the uncertainty model set identification and the stable controller design. Firstly the worst case υ-gap is used as the criterion of the optimal excitation signals design, and the design is performed via the power spectrum optimization. And then, an uncertainty model set is attained by system identification on the basis of the measure signals. The controller is designed to ensure the stability of closed-loop system and the closed-loop performance improvement. Simulation result shows that the proposed method has good convergence and closed-loop control performance. Supported by the National Natural Science Foundation of China (Grant Nos. 60574055, 60874073), the Specialized Research Fund for Doctoral Program of Higher Education of China (Grant No. 20050056037), and the Tianjin Science and Technology Keystone Project (Grant No. 08ZCKFJC27900)     

An adaptive multipath routing scheme for connectionless traffic in an ATM network

This paper addresses the problem of routing connectionless traffic through an ATM network. A solution is proposed based on a per-packet adaptive multipath routing scheme which is added to the routing algorithm implemented at the Inter-Working Units. A scheme is presented that distributes packets among multiple Virtual Paths (VPs) according to the utilization of the links on these VPs. The utilization of the VPs is determined by a periodic feedback mechanism. Simulation studies show the effectiveness of the proposed adaptive multipath routing scheme.The work by J. Sole-Pareta was supported in part by a CIRIT (Generalitat de Catalunya) grant (expedient number EE92/2-338), and in part by the National Science Foundation under Grant No. INT-94033646. The work by I. Akyildiz was supported in part by the National Science Foundation under Grant No. INT-94033646.