SNePSwD: A newcomer to the SNePS family

Abstract

SNePS 2.1 is a knowledge representation and reasoning system that records the dependencies among propositions that are needed to perform a revision of beliefs when a contradiction is detected. The reasoning of SNePS 2.1 is based on a monotonic logic and the system has no provisos for performing an automatic revision of beliefs. In this paper we present SNePSwD that extends the capabilities of SNePS 2.1 along two dimensions: (1) it is able to represent default rules and to perform default reasoning, i.e. the logic underlying SNePSwD is non-monotonic; (2) it accepts the specification of preferences between hypotheses and uses them to decide which hypotheses to discard to resolve a contradiction. This latter possibility allows a semi-automatic contradiction resolution (in some cases, even completely automatic). We discuss the motivations for the creation of SNePSwD, present the form of default rules it uses, discuss the meaning of each of the three kinds of consequence, and describe how preferences can be specified among propositions and how these preferences are used in the process of belief revision. Finally we present examples that illustrate the aspects discussed in the paper.     

用于软件维护的程序更新工具

随着计算机在各个行业中的广泛运用和计算机科学技术的迅猛发展,软件维护成本在整个系统生命周期成本中占有越来越大的份额。本文针对现有的编辑工具中替换功能不支持通配符和多行替换等问题,提出了一套用于软件维护的程序更新方法。利用这一方法能有效地提高软件维护业务的效率,降低维护成本。     

FUNCTIONAL OBSERVERS FOR LINEAR SYSTEMS WITH UNKNOWN INPUTS

In this paper, a straightforward approach is presented to design functional observers for linear systems with unknown inputs. Necessary and sufficient conditions are provided for the existence of the observers. Some illustrated examples are included.     

推理维护系统的Petri网模型

本文为推理维护系统引入一种Ｐｅｔｒｉ网模型并对有限非单调理论应用Ｐｅｔｒｉ例分析方法．本文提议的模型不但能描述推理维护系统，而且可用网论与网技术分析推理维护．对于一组给定的非单调规则我们给出一个算法可求得其外延，我们还给出一个算法可发现系统的不一致性．我们提出的寻找外延的算法要比现有的重构过程更有效，且它是可判定的．     

一类具有不确定性的非线性相似组合系统的鲁棒镇定

描述了两个控制系统间的相似性概念,讨论了一类具有不确定性的非线性相似组合系统的鲁棒镇定问题.结果表明,作者构造的控制器具有结构相似性.相似结构确实可以简化组合系统鲁棒镇定的判据.这说明,在一定程度上,具有相似结构的组合系统其相似结构具有稳固系统的特性.     

具有不确定性的非线性系统的变结构控制

本文研究了具有不确定性非线性系统的鲁棒输出跟踪控制问题，考虑了对参数、建模不确定性及干扰的鲁棒性。这里的不确定性不需满足通常的匹配条件。通过构造一个Ｌｙａｐｕｎｏｖ函数，我们得到一个变结构控制器，并且证明了输出跟踪误差的收敛性。最后，给出了计算机仿真，结果表明本文提出的方法是有效的。     

认识逻辑(1):关于知识和信念的逻辑框架

知识和信念是人工智能领域研究中经常涉及到的两个重要概念。本文讨论了知识和信念的涵义与关系，定义了认识逻辑系统ＥＩ，讨论了它的语法和语义，证明了认识逻辑ＥＬ不但是可靠的而且是完备的，认为逻辑ＥＬ不但可以用来描述人类的认识过程，还可以用于对常识推理以及分布式系统的形式化描述。     

具有多个时变时滞的不确定系统的时滞相关稳定性

研究了具有多个时变时滞的不确定系统的 稳定性问题, 利用Razumikhn定理与向量不等式的方法, 给出了不确定时滞系统稳定的充分 条件. 所得的条件与时滞相关, 在很大程度上降低了现有结果的保守性. 文末给出了一个应 用的算例, 并与已有的结果作了比较.     

不确定时变时滞组合系统的鲁棒分散控制

研究一类互联项与孤立子系统均含有时变状态时滞的不确定组合系统的状态反馈 鲁棒分散控制问题,利用线性矩阵不等式（LMI）方法设计出线性无记忆状态反馈分散控制 器使受控系统在平衡点处渐近稳定．最后给出的数值例子验证了所给结果的有效性．     

结构不确定线性系统的鲁棒性分析

基于一种向量的幂变换方法，对具有结构不确定性的线性系统的鲁棒稳定和Ｄ稳定性问题进行了分析，给出了系统鲁棒稳定和Ｄ稳定区域的代数表达形式，最后给出了算例。     

SIMPLE INSTABILITY CRITERION FOR A CLASS OF SINGULAR SYSTEMS WITH MULTIPLE TIME DELAYS

In this paper, the instability for a class of singular systems with discrete and distributed time delays is investigated. Simple instability criterion, which is a delay‐dependent criterion, is derived to guarantee the instability of such systems. Finally, a numerical example is given to illustrate the use of the main result.     

一类非线性相似组合系统的鲁棒分散控制器的设计

对于一类非线性组合系统提出了系统的相似性结构的定义,讨论了这类具有相似性结构的非线性结构不确定组合系统的鲁棒分散镇定问题.利用系统的相似性结构,采用输入、输出线性化与滑模控制原理相结合的方法所设计出的鲁棒分散控制器可确保闭环系统是渐近稳定的.研究结果表明系统的相似性结构使设计的滑动面和分散控制器亦具有相似结构,从而简化了对系统的分析与设计.     

秩-1型不确定性时滞系统鲁棒控制器设计——LMI方法

1　引言由于工程系统中大量存在时滞现象,有关时滞系统的报道愈来愈多,采用黎卡提方程方法研究时滞系统的鲁棒控制问题在近一、二十年一直是控制领域的研究热点之一[1].应用黎卡提方程方法时,有关参数的选取直接关系到所得结果的好坏,但如何找到合适参数的问题至今没有解决.而近几年发展成熟的线性矩阵不等式(LMI)方法不需要调整参数就可得到问题的解,因此用LMI方法研究时滞系统鲁棒控制问题的文献相继出现[2—3].尽管不确定性时滞系统鲁棒控制方面的报道很多,但大部分结果与系统时滞无关[1—3],这些独立于时滞的结论无疑是保守的,而依赖…     

不确定组合大系统的自适应分散镇定控制

考虑具有非线性关联作用的不确定时变线性组合大系统的自适应分散镇定问题.针对系统不确定界完全未知的情形,首先从理论上证明了可设计自适应鲁棒分散控制器确保受控系统渐近稳定;进而从工程实际应用的角度,给出了确保受控系统实用稳定的自适应鲁棒分散控制器的设计方案.仿真说明该设计方案是有效的.     

具有最小相位的非线性时变不确定系统的鲁棒镇定

讨论了含有时变未知参变数或扰动的非线性不确定系统的鲁棒镇定问题。     

时变时滞不确定系统基于观测器的鲁棒控制器设计

研究了时变时滞不确定系统基于状态观测器的 鲁棒控制器设计问题, 其中不确定性是时变的,满足范数有界条件. 利用Lyapunov稳定性 理论和Razumikhin-type理论,获得了基于状态观测器的鲁棒控制器存在条件, 以及给出了 相应的控制律. 所得结论推广并改进了已知的一些结果. 通过实例说明了其有效性.     

REDUCED‐ORDER MODELS FOR FEEDBACK STABILIZATION OF LINEAR SYSTEMS WITH A SINGULAR PERTURBATION MODEL

The problem of output feedback stabilization of linear systems based on a reduced‐order model is addressed in this paper. New reduced‐order models are proposed for the output feedback design of linear systems with a singular perturbation model. An output feedback controller with a zero steady‐state gain matrix is proposed for stabilizing this kind of system. It is shown that with the proposed controller the reduced‐order model based feedback design can guarantee the actual closed‐loop stability for the sufficiently small perturbation parameter. This approach can overcome the difficulties in the existing design method using the so‐called zeroth‐order approximation model, whose validity is highly dependent on the value of the perturbation parameter.     

基于高次神经网络的一类非线性组合大系统的鲁棒控制器设计

对于一类非线性组合大系统,本文提出了基于 高次神经网络的一种新型控制器的设计方法．本文首先用高次神经网络逼近非线性组合大系 统中的互联项,然后基于高次神经网络设计一种新型控制器,这种设计方法不仅解决了大系 统中的最为复杂的互联项问题,较以往采用的办法在工程上易于实现．仿真结果表明了该方 法的有效性．     

A GENERAL TELEOLOGICAL PRINCIPLE FOR DYNAMICAL SYSTEMS

Abstract

We define a class of physical processes with a causal as well as a teleological component. A causal law generates a set of possible future states of a system when an initial state is given. If the law is deterministic, then different possible future states are obtained if minor variations of the initial state are taken. Possible futures are allowed to interfere with each other. Then, one possible future state is selected according to a deterministic or a nondeterministic selection criterion. The next state of the system is either the possible future state that has been selected, or an intermediate state taken by the system when it evolves to this state. This general scheme can be used to obtain teleological variations of many dynamical systems in which a function is maximized or minimized. We consider two concrete examples. As a first example, we consider a teleological variation of an algorithmic growth process. We show that a teleological algorithm leads to forms with higher values for a quality measure than the non-teleological process from which it is derived. The second example belongs to the cognitive domain. It is shown that a teleological variation of the connectionist backpropagation learning rule leads to significantly lower values for the error function of a network, and hence to a weight matrix of better quality than ordinary backpropagation. On a more basic level, it is conjectured that the type of teleology that is considered can be related to irreversibility in physics.     

OPTIMAL TRACKING CONTROL FOR DISCRETE TIME‐DELAY SYSTEMS WITH PERSISTENT DISTURBANCES

Optimal tracking control (OTC) for discrete time‐delay systems affected by persistent disturbances with quadratic performance indexes is considered. Optimal tracking controller is designed based on a sensitivity approximation approach. By introducing a sensitivity parameter, we transform the original OTC problem into a series of difference equations without time‐advance on time‐delay terms. The obtained OTC law consists of analytic feedback and feedforward terms, and a compensation term, which is the sum of the infinite series of adjoint vectors. The compensation term can be obtained with an iterated formula for the adjoint vectors. A simulation example shows that the approximation approach is effective in tracking the reference input and robust with respect to exogenous persistent disturbances.