大系统动态递阶控制设计

本文在[1]的模型基础上,研究了当系统具有二次性能指标时如何设计动态递阶控制问题,提出了动态递阶控制模型和三级递阶算法,并详细讨论了它的性质和收敛性问题,该模型和算法克服了文献[2]中的缺陷。     

大系统的多级递阶控制

本文对大系统多级递阶控制概念、分解、协调原则、统一算法的探讨、Stackelberg策略的应用、闭环控制等有关多级递阶控制的五个基本问题,作了较详细的介绍。最后,作者提出了某些讨论性意见。     

线性大系统递阶控制的一种新型逼近方法

将文[1]提出的按段多重契比雪夫多项式系(PMCP)应用于线性大系统递阶控制算法的 逼近计算,将动态递阶控制转化为静态递阶优化,获得了一种新型逼近算法.仿真结果表明 了该算法的有效性.     

动态大系统递阶实时控制的新算法及其实现

本文采用了一种新的适用于实时在线控制的递阶算法,并在分布式计算机控制系统上予以实现.应用这种算法,可减少两级之间通讯的信息量,使控制级任务减轻,协调级的计算简单,收敛速度快,局部任务的选择自由度大.本文所设计的分布式计算机控制系统具有通讯可靠,易于扩充、维护等优点.实验证明,用该系统实现实时动态大系统的递阶控制有较理想的结果.     

专家系统与智能控制在“铁鸟”系统中的应用

本文介绍了航空“铁鸟”工程系统的特点与综合性控制问题,论述了专家系统与智能控制技术在“铁鸟”系统的故障诊断.过程监控和分级递阶协调控制方面的应用,着重介绍了分级递阶智能控制系统和三种主要智能适应控制器的设计方法和信息结构.本文提出的控制方法已在实际系统中得到了成功的应用.     

大系统的动态递阶控制

本文提出了一种镇定线性大系统的动态递阶控制新方案.对于分散控制线性大系统,如 果是可控可观的,则可以设计一个上一层系统,并能确定它的最小维数,使所产生的新系统在 递阶控制下无固定模,从而能够得到一个协调控制器,使整个闭环系统能任意配置极点.这种 新的大系统动态递阶控制具有实际意义,其递阶控制器的设计也简单易行.     

复杂系统的递阶模糊辨识

针对Takagi_Sugeno模糊模型 (T_S模型 )严重的维数灾问题, 借鉴GMDH算法, 提出了一种新的复杂系统递阶模糊辨识方法. 本文首先详细描述了由两输入变量的特殊T_S模型所组成的递阶模糊模型 ;然后提出了具体的辨识该递阶模糊模型的方法. 该方法的特点是 :a)在结构辨识阶段, 用FCM模糊聚类方法评价系统中每个输入变量的重要性, 以便构造合理的递阶模糊模型 ;b)预先合理地确定了所要辨识的参数的初始值, 用扩展卡尔曼滤波方法可很快地得到这些参数. 最后, 给出的仿真实例说明了本文辨识方法的有     

非整数阶系统频域辨识的递推最小二乘算法

非整数阶系统辨识方法是建立非整数阶系统模型的一种重要工具．本文提出了一种非整数阶系统频域辨识的最小二乘递推算法．给出了算法的详细推导，并用已知系统验证了算法的有效性．结果表明该算法是整数阶系统辨识的最小二乘递推算法的推广．使用此算法，不但能辨识整数阶系统，还能辨识非整数阶系统．     

一种闭环条件下的多变量系统辨识方法

为得到带有色噪声的闭环多变量系统参数无偏估计,提出两阶段随机梯度辨识算法,此算法利用中间模型将闭环问题转化成两个开环问题,并基于随机梯度算法和递阶辨识原则,用最速下降法极小化预测误差准则来得到参数估计.算法只需一个测试信号,不需要控制器的先验知识,计算简便,能获得满意的结果,适用于闭环多变量系统的在线辨识.     

粗糙集理论的分层递阶约简算法及其信息理论基础

本文模拟人类认知的分层递阶原则,提出一种粗糙集理论的分层递阶约简算法.该算法首先将信息系统或决策系统的知识在由部分属性所构成的多种层次和多种粒度上表示出来,然后分别对各个属性层次进行递阶约简.因此,该算法具有较强的实用性和较好的动态特性,并且能并行运算.同时,本文从信息理论的角度证明了分层递阶约简的理论基础.文章的最后将该算法应用于某水泥窑炉控制决策的获取中,证实了其有效性.     

A sequential method for system identification in hierarchical structure

Implicit in all of hierarchical systems theory is the idea that it is generally easier to deal with several low order systems than with one system of high order. The basic idea of hierarchical systems theory is to decompose a large dimensional system into smaller dimensioned sub-systems in such a way that the overall system objectives can be met.

This paper is concerned with the application of hierarchical system theory to the identification problem. Specifically, the equations associated with a given identification problem are recast such that they may be decomposed into infimal subproblems of system identification which can be coordinated using hierarchical systems theory.

The maximum a posteriori approach to system identification is taken. This leads to a two point boundary value problem solution which determines optimum state and parameter estimates and estimates of any unknown prior statistics. Invariant imbedding is used to resolve this two point boundary value problem such that a recursive or sequential solution to the identification problem is obtained. Several examples indicate the use of the identification algorithms.     

Optimization of I/O systems by cache disks and file migration: A summary

The file system, and the components of the computer system associated with it (disks, drums, channels, mass storage, tapes and tape drives, controllers, I/O drivers, etc.) comprise a very substantial fraction of most computer systems; substantial in several aspects, including amount of operating system code, expense for components, physical size and effect on performance. In a companion paper, we surveyed the traditional methods for optimizing the I/O system. We then examined disk and I/O system architecture in IBM type systems, and indicated shortcomings and future directions. In this paper we go one step further and summarize research by the author on two topics: cache disks and file migration. Cache disks are disks which have an associated cache which buffers recently used tracks of data. The case for cache disks is presented, and some of the issues are discussed. Parameter values for some aspects of the cache design are suggested. The second part of this paper summarizes the author's work on file migration, by which files are migrated between disk and mass storage as needed in order to effectively maintain on-line a much larger amount of information than the disks can hold. Some of the algorithms investigated are discussed, and the basic results are presented.     

Optimization of I/O systems by cache disks and file migration: A summary

The file system, and the components of the computer system associated with it (disks, drums, channels, mass storage tapes and tape drives, controllers, I/O drivers, etc.) comprise a very substantial fraction of most computer systems; substantial in several aspects, including amount of operating system code, expense for components, physical size and effect on performance. In a comparison paper, we surveyed the traditional methods for optimizing the I/O system. We then examined disk and I/O system architecture in IBM type systems, and indicated shortcomings and future directions. In this paper we go one step further and summarize research by the author on two topics: cache disks and file migration. Cache disks are disks which have an associated cache which buffers recently used tracks of data. The case for cache disks is presented, and some of the issues are discussed. Parameter values for some aspects of the cache design are suggested. The second part of this paper summarizes the author's work on file migration, by which files are migrated between disk and mass storage as needed in order to effectively maintain on-line a much larger amount of information than the disks can hold. Some of the algorithms investigated are discussed, and the basic results are presented.     

Hierarchical classification in text mining for sentiment analysis of online news

Sentiment analysis in text mining is a challenging task. Sentiment is subtly reflected by the tone and affective content of a writer’s words. Conventional text mining techniques, which are based on keyword frequencies, usually run short of accurately detecting such subjective information implied in the text. In this paper, we evaluate several popular classification algorithms, along with three filtering schemes. The filtering schemes progressively shrink the original dataset with respect to the contextual polarity and frequent terms of a document. We call this approach “hierarchical classification”. The effects of the approach in different combination of classification algorithms and filtering schemes are discussed over three sets of controversial online news articles where binary and multi-class classifications are applied. Meanwhile we use two methods to test this hierarchical classification model, and also have a comparison of the two methods.     

On hierarchical estimation and system identification using the MAP criterion

This paper presents a general treatment of hierarchically structured maximum-a posteriori (MAP) estimation and system parameter identification algorithms for large-scale systems. Continuous-time and discrete-time algorithms for hierarchical estimation and system identification in large-scale systems are derived for several supremal infimal coordination methods. Consolidation and unification of previous results in hierarchical systems theory as applied to system identification are accomplished. Numerical examples are considered to demonstrate the effectiveness of the algorithms which are potentially of considerable utility in computer modeling of large systems.     

Hierarchically consistent control systems

Large-scale control systems typically possess a hierarchical architecture in order to manage complexity. Higher levels of the hierarchy utilize coarser models of the system, resulting from aggregating the detailed lower level models. In this layered control paradigm, the notion of hierarchical consistency is important, as it ensures the implementation of high-level objectives by the lower level system. In this paper, we define a notion of modeling hierarchy for continuous control systems and obtain characterizations for hierarchically consistent linear systems with respect to controllability objectives. As an interesting byproduct, we obtain a hierarchical controllability criterion for linear systems from which we recover the best of the known controllability algorithms from numerical linear algebra     

分时EDF算法及其在多媒体操作系统中的应用

提出了一种新的CPU调度算法－－分时EDF（Earliest Deadine First)算法,该算法能保证硬实时任务不丢失死线,并易于在分时系统中实现。以分时EDF算法为基础,提出一种新的CPU层次调度算法－－HRFSFQ,该算法用于多媒体操作系统时能保证各类任务的QoS。最后通过大量实验证明了上述算法的有效性和正确性。     

Mathematical modeling and heuristic approaches to flexible job shop scheduling problems

Scheduling for the flexible job shop is very important in both fields of production management and combinatorial optimization. However, it is quite difficult to achieve an optimal solution to this problem in medium and actual size problem with traditional optimization approaches owing to the high computational complexity. For solving the realistic case with more than two jobs, two types of approaches have been used: hierarchical approaches and integrated approaches. In hierarchical approaches assignment of operations to machines and the sequencing of operations on the resources or machines are treated separately, i.e., assignment and sequencing are considered independently, where in integrated approaches, assignment and sequencing are not differentiated. In this paper, a mathematical model and heuristic approaches for flexible job shop scheduling problems (FJSP) are considered. Mathematical model is used to achieve optimal solution for small size problems. Since FJSP is NP-hard problem, two heuristics approaches involve of integrated and hierarchical approaches are developed to solve the real size problems. Six different hybrid searching structures depending on used searching approach and heuristics are presented in this paper. Numerical experiments are used to evaluate the performance of the developed algorithms. It is concluded that, the hierarchical algorithms have better performance than integrated algorithms and the algorithm which use tabu search and simulated annealing heuristics for assignment and sequencing problems consecutively is more suitable than the other algorithms. Also the numerical experiments validate the quality of the proposed algorithms.     

普适评估算法模型的实现

本文论述的评估算法模型主要针对常用的各类评估系统。这些算法模型有多种形式。文中详细地给出了其实现算法。这些算法模型具有很强的实用性。能为建立高效和功能强大的计算机评估系统提供参考。     

Enabling hierarchical dissemination of streams in content distribution networks

In streaming systems the content distribution network routes streams based on interests registered by the consuming entities. In hierarchical streaming, the dissemination is also predicated on the resolution of hierarchical dependencies between various streams. Entities specify explicit wildcards, in addition to the implicit ones in place, to further control the types of streams within a given hierarchy that should be routed to them. This paper presents an analysis and performance evaluation of three different algorithms for hierarchical streaming. In our evaluation of these algorithms we are especially interested in three factors: performance, ability to cope with flux, and memory consumption. Comprehensive benchmarks for these algorithms, in this paper, will enable system designers to harness the best algorithm that satisfies their hierarchical streaming requirements. Copyright © 2011 John Wiley & Sons, Ltd.