Adaptive predictive control algorithm based on Laguerre Functional Model

Laguerre Functional Model has many advantages such as good approximation capability for the variances of system time‐delay, order and other structural parameters, low computational complexity, and the facility of online parameter identification, etc., so this model is suitable for complex industrial process control. A series of successful applications have been gained in linear and non‐linear predictive control fields by the control algorithm based on Laguerre Functional Model, however, former researchers have not systemically brought forward the theoretical analyses of the stability, robustness, and steady‐state performance of this algorithm, which are the keys to guarantee the feasibility of the control algorithm fundamentally. Aimed at this problem, we introduce the principles of the Incremental Mode Linear Laguerre Predictive Control (IMLLPC) algorithm, and then systemically propose the theoretical analyses and proofs of the stability and robustness of the algorithm, in addition, we also put forward the steady‐state performance analysis. At last, the control performances of this algorithm on two different physical industrial plants are presented in detail, and a number of experimental results validate the feasibility and superiority of IMLLPC algorithm. Copyright © 2005 John Wiley & Sons, Ltd.     

STUDY ON RESIDUES OF ~（14）C－FENITROTHION IN MODEL RICE－FISH ECOSYSTEM AND FIELD RICE－FISH ECOSYSTEM

ＳＴＵＤＹＯＮＲＥＳＩＤＵＥＳＯＦ~（１４）Ｃ－ＦＥＮＩＴＲＯＴＨＩＯＮＩＮＭＯＤＥＬＲＩＣＥ－ＦＩＳＨＥＣＯＳＹＳＴＥＭＡＮＤＦＩＥＬＤＲＩＣＥ－ＦＩＳＨＥＣＯＳＹＳＴＥＭＺｈａｎｇＺｈｏｎｇｌｉａｎｇ（张仲良）；ＷａｎｇＨｕａｘｉｎ（王化新）；Ｇ?..     

一种结合知识挖掘的进化规划算法

进化规划是一种进化计算方法。进化规划主要使用随机化技术来实现优化过程。与其它进化算法相比,进化规划只有变异操作,而没有交叉操作,因此变异操作的有效性对进化规划算法的成功至关重要。在传统进化规划算法中,进化规划的变异操作具有完全的随机性,这虽然有利于避免局部极值,但却导致较大的计算量。在本文算法中,将知识挖掘技术引入进化规划之中。知识挖掘技术主要用于发现规则,然后利用发现的规则指导变异操作过程,提高变异操作的效率。最终加快了进化规划算法的速度,而计算效果没有明显下降。通过知识挖掘技术的引入,进化规划算法有了初步的智能特性。将本文所介绍的新算法应用于视频编码的运动估计实验中,结果表明新算法有良好的计算速度和计算精确性。     

AutoCAD图形的打印输出技巧

针对AutoCAD使用者出图时所遇到的问题,提供了两种不同的解决方法.     

Efficient model reduction in non-linear dynamics using the Karhunen-Loève expansion and dual-weighted-residual methods

 We look at the task of computing the time-evolution of a non-linear system for a long time, in our case under random external influences. Our specific example is the fatigue evaluation of a wind turbine. To facilitate such a computation, we look at a reduction of the computational effort by projecting everything on a low-dimensional basis. In this case we take the Karhunen-Loève basis generated from running the model a little while under the random loading. It is important that the error which is caused by this reduction process can be controlled. We estimate the error by dual or adjoint methods. This in turn allows the process of model reduction to be performed adaptively. Dedicated to the memory of Prof. Mike Crisfield, for his cheerfulness and cooperation as a colleague and friend over many years.     

Distributed Speech Recognition Systems and Some Key Factors Affecting It''''s Performance

1　IntroductionWiththerapiddevelopmentofInternetandmobilecommunications,theresearchonwirelessmobilenetworkshasbecomethenewhotspotinin formationtechnologyfield .Asweknow ,mobileterminals (mobilephone,forexample)arethetooltohelppeopletoaccessanyinformationtheyneedbyanymediaatanytimeandanywhere .However,itissometimesdifficultformobileterminalstoplaysucharolebecauseofthelimitationssuchaslimitedca pacity ,lowpower,andinconvenienceinoperating .So,peoplehopetofindanotherwaytoaccessnet workinformatio…     

支持向量机中的模型选择研究

支持向量机是一种新型的机器学习方法。模型选择是设计支持向量机的关键。本文在分析用于分类的支持向量机原理的基础上,分别从核函数类型和核参数的选择等模型选择方面进行了探讨。最后在上述理论分析的基础上进行了实验,取得了较好的效果。     

A new approach for sequential experimental design for model discrimination

Model discrimination procedures are useful tools for selection of the best mathematical models to be used to represent a specific chemical process. The present paper presents and discusses a new sequential discrimination procedure, which makes use of model probabilities and concentrates the efforts on models with higher probabilities. Model probabilities are determined based on simple statistical arguments. Four numerical examples illustrate the application of the proposed discrimination procedure. The obtained results indicate that the new procedure is able to discriminate kinetic models with fewer experiments when compared to other procedures and also indicates when model discrimination is not possible and, thus, when the sequential design must be halted. Furthermore, the speed of the proposed discrimination procedure can be controlled by tuning a design parameter which reflects the analyst's mood (confidence) towards the discrimination problem and allows for increase or decrease of the number of experiments required for model discrimination during the sequential procedure.     

High accuracy path tracking for vehicles in presence of sliding: Application to farm vehicle automatic guidance for agricultural tasks

When designing an accurate automated guidance system for vehicles, a major problem is sliding and pseudo-sliding effects. This is especially the case in agricultural applications, where five-centimetre accuracy with respect to the desired trajectory is required, although the vehicles are moving on slippery ground. It has been established that RTK GPS was a very suitable sensor to achieve automated guidance with such high precision: several control laws have been designed for vehicles equipped with this sensor, and provide the expected guidance accuracy as long as the vehicles do not slide. In previous work, further control developments have been proposed to take sliding into account: guidance accuracy in slippery environments has been shown to be preserved, except transiently at the beginning/end of curves. In this paper, the design of this control law is first recalled and discussed. A Model Predictive Control method is then applied in order to preserve accuracy of guidance even during these curvature transitions. Finally, the overall control scheme is implemented, and improvements with respect to previous guidance laws are demonstrated through full-scale experiments.     

精镗孔尺寸误差预测补偿技术的研究概况与趋势

提出了精镗孔尺寸误差预测补偿技术存在的主要问题，指出了今后所需研究的主要内容及关键技术。