K(Knowledge)-net: building up and its dynamics

The essence of intelligence is to use certain abilities to obtain knowledge, to use that knowledge, and to operate with that knowledge. New knowledge learned by a human is often related to old existing knowledge, and sometimes we could have more conceptual knowledge based on old knowledge. So, the knowledge in the brain exists in a related structural form, and this structure is dynamic, and therefore is evolvable. Based on the understanding of the real process of learning by a human being, we discuss how to make a model to describe the dynamic structure of knowledge. This model is also a principle of artificial brain design. Most of the knowledge a child learns is from natural language and perception information, and we define this as semantic knowledge. The model to describe the process and structure of knowledge growing in a network form is called a K-net. It is a dynamic network with two main dynamics: one is new knowledge added, and the other is aggregating knowledge existing in the network with some probability. Under these very natural conditions, we found that the network is originally a simple random net, and then some characteristics of a complex network gradually appear when more new knowledge is added and aggregated. A more interesting phenomenon is the appearance of a random hierarchical structure. Does this mean emergence?     

混合关系中的函数依赖及其相关规则

在实际应用中有这样一类关系数据库,其中数据项在某个属性上的取值本身又是一个关系。讨论这种混合关系中的函数依赖及其相应的相关规则具有一定的理论意义和实际应用价值。给出这种混合关系的形式定义、混合关系中4种类型的函数依赖关系以及相应的4种类型的相关规则;并给出混合关系到一般关系的转换,通过这个转换说明了混合关系与普通关系的联系及其差别。给出一个实际应用中的例子,来说明混合关系中的函数依赖和相关规则的形式多样性。     

基于通用比较模型的t-可诊断系统的特征化及并行诊断算法

文中介绍了一种系统级故障诊断模型－－通用比较模型,该模型处理器作为自身的比较器,综合经典的ＰＭＣ模型和Ｍａｅｎｇ／Ｍａｌｅｋ模型的优点,基于该报多处理器系统的ｔ＿可诊断性问题,给出了ｔ＿可诊断系统的特征化,证明了一个系统成为ｔ－可诊断系统的新的充分必要条件,其次,证明在通用比较模型中,确定故障顺集的问题等价于求解一个超图的最小横切集（Ｍｉｎｉｍｕｍ ｔｒａｖｅｒｓａｌ）,该超图是根据多处理器的通信     

Vague集的模糊逼近与模糊熵

给出了vague集转换为模糊集的一种新的方法,定义了vague集的模糊逼近。利用vague集的模糊逼近研究了vague集的模糊熵及其相关性质。     

Distributed speculative execution for reliability and fault tolerance: an operational semantics

This paper examines the use of speculations, a form of distributed transactions, for improving the reliability and fault tolerance of distributed systems. A speculation is defined as a computation that is based on an assumption that is not validated before the computation is started. If the assumption is later found to be false, the computation is aborted and the state of the program is rolled back; if the assumption is found to be true, the results of the computation are committed. The primary difference between a speculation and a transaction is that a speculation is not isolated—for example, a speculative computation may send and receive messages, and it may modify shared objects. As a result, processes that share those objects may be absorbed into a speculation. We present a syntax, and an operational semantics in two forms. The first one is a speculative model, which takes full advantage of the speculative features. The second one is a nonspeculative, nondeterministic model, where aborts are treated as failures. We prove the equivalence of the two models, demonstrating that speculative execution is equivalent to failure-free computation.     

An Order-Based Theory of Updates for Closed Database Views

The fundamental problem in the design of update strategies for views of database schemata is that of selecting how the view update is to be reflected back to the base schema. This work presents a solution to this problem, based upon the dual philosophies of closed update strategies and order-based database mappings. A closed update strategy is one in which the entire set of updates exhibit natural closure properties, including transitivity and reversibility. The order-based paradigm is a natural one; most database formalisms endow the database states with a natural order structure, under which update by insertion is an increasing operation, and update by deletion is decreasing. Upon augmenting the original constant-complement strategy of Bancilhon and Spyratos – which is an early version of a closed update strategy – with compatible order-based notions, the reflection to the base schema of any update to the view schema which is an insertion, a deletion, or a modification which is realizable as a sequence of insertions and deletions is shown to be unique and independent of the choice of complement. In addition to this uniqueness characterization, the paper also develops a theory which identifies conditions under which a natural, maximal, update strategy exists for a view. This theory is then applied to a ubiquitous example – single-relational schemata constrained by equality-generating dependencies. Within this framework it is shown that for a view defined as a projection of the main relation, the only possibility is that the complement defining the update process is also a projection, and that the reconstruction is based upon functional dependencies.     

Crab walking of quadruped robots with a locked joint failure

Fault tolerance is an important aspect in the development of control systems for multi-legged robots since a failure in a leg may lead to a severe loss of static stability of a gait. In this paper, an algorithm for tolerating a locked joint failure is described in gait planning for a quadruped robot with crab walking. A locked joint failure is one for which a joint cannot move and is locked in place. If a failed joint is locked, the workspace of the resulting leg is constrained, but legged robots have fault tolerance capability to continue walking maintaining static stability. A strategy for fault-tolerant gaits is described and, especially, a periodic gait is presented for crab walking of a quadruped. The leg sequence and the formula of the stride length are analytically driven based on gait study and robot kinematics. The adjustment procedure from a normal gait to the proposed fault-tolerant crab gait is shown to demonstrate the applicability of the proposed scheme.     

基于认知理论和随机开放性测试的动态学生建模研究

论文从认知理论出发,提出了一种实用的学生建模方法,即以信息模型和学习模型的组合形式进行学生建模,并采用认知模型、覆盖模型和测试模型对学习模型进行描述。该学生模型可以很好地实现学生模型的动态修改以及教学策略的自适应调整。文中对基于随机算法的开放性测试进行了研究,给出了它的实现算法,并进一步讨论了基于此算法的学生模型修改策略。最后,讨论了基于认知理论与随机开放性测试的动态学生模型在ICAI中的实践,建立了一个ICAI集成教学系统。     

辨识非线性曲线的非线性极大似然—优化法

工程上经常碰到非线性曲线辨识问题。本文探讨一种非线性极大似然-优化法并结合三次样条函数拟配法,形成统一的逐次逼近的直接辨识非线性曲线的非线性辨识方法。该法兼有极大似然法的唯一性、很好的收敛性和优化法直接处理非线性系统的能力,辨识出的样条函数曲线能无限地光滑地逼近非线性曲线。     

A systemic approach to integrated E-maintenance of large engineering plants

Large engineering plants (LEPs) have certain unique features that necessitate a maintenance strategy that is a combination of both time and condition based maintenance. Although this requirement is appreciated to varying degrees by asset owners, applied research leading to a systematic development of such a maintenance strategy is the need of the day. Such a strategy should also adopt a wholesome ``systemic' approach so that the realization of the overall objectives of maintenance is maximized. E-maintenance has several potential benefits for large engineering plants. In this paper, a three pronged strategy is suggested for the successful implementation of e-maintenance for LEPs. Firstly, an integrated condition and time based maintenance framework is proposed for LEPs. Secondly, reference is drawn to models for condition and time based maintenance at systemic levels. As a part of the ab initio development of a condition monitoring system for a LEP, one of the characteristics of the condition monitoring system, namely, predictability, is discussed in detail as a sample for a systemic study. Thirdly, emphasis is laid on the information and expertise available in the domain of plant design, operation and maintenance and the same is tapped for incorporation in maintenance decision making.     

Nonlinear system identification via direct weight optimization

A general framework for estimating nonlinear functions and systems is described and analyzed in this paper. Identification of a system is seen as estimation of a predictor function. The considered predictor function estimate at a particular point is defined to be affine in the observed outputs and the estimate is defined by the weights in this expression. For each given point, the maximal mean-square error (or an upper bound) of the function estimate over a class of possible true functions is minimized with respect to the weights, which is a convex optimization problem. This gives different types of algorithms depending on the chosen function class. It is shown how the classical linear least squares is obtained as a special case and how unknown-but-bounded disturbances can be handled.Most of the paper deals with the method applied to locally smooth predictor functions. It is shown how this leads to local estimators with a finite bandwidth, meaning that only observations in a neighborhood of the target point will be used in the estimate. The size of this neighborhood (the bandwidth) is automatically computed and reflects the noise level in the data and the smoothness priors.The approach is applied to a number of dynamical systems to illustrate its potential.     

Using genetic algorithm for lot sizing and scheduling problem with arbitrary job volumes and distinct job due date considerations

This paper considers an integrated lot sizing and scheduling problem for a production–distribution environment with arbitrary job volumes and distinct due dates considerations. In the problem, jobs are firstly batch processed on a batching machine at production stage and then delivered to a pre-specified customer at the subsequent delivery stage by a capacitated vehicle. Each job is associated with a distinct due date and a distinct volume, and has to be delivered to the customer before its due date, i.e. delay is not allowed. The processing time of a batch is a constant independent of the jobs it contains. In production, a constant set-up time as well as a constant set-up cost is required before the first job of this batch is processed. In delivery, a constant delivery time as well as a constant delivery cost is needed for each round-trip delivery between the factory and the customer. Moreover, it is supposed that a job that arrives at the customer before its due date will incur a customer inventory cost. The objective is to find a coordinated lot sizing and scheduling scheme such that the total cost is minimised while guaranteeing a certain customer service level. A mixed integer formulation is proposed for this problem, and then a genetic algorithm is developed to solve it. To evaluate the performance of the proposed genetic algorithm, a lower bound on the objective value is established. Computational experiments show that the proposed genetic algorithm performs well on randomly generated problem instances.     

基于反步法的移动机器人鲁棒跟踪控制

以四轮移动机器人为研究对象,建立了机器人完整的数学模型,包括运动学模型、动力学模型以及驱动电机模型。在机器人数学模型的基础上,采用反步法的思想设计具有全局收敛特性的鲁棒轨迹跟踪控制器,设计中考虑了驱动电机模型使控制器更符合实际控制要求,并将其分解为运动学控制器、动力学控制器以及电机控制器三部分,降低了控制器设计的难度。构造了系统的李雅普诺夫函数,证明了该类型移动机器人在所得控制器作用下,能实现对给定轨迹的全局渐近追踪。仿真实验结果表明基于反步法的控制器是有效的。     

Robust graph coloring based on the matrix semi-tensor product with application to examination timetabling

This paper investigates the robust graph coloring problem with application to a kind of examination timetabling by using the matrix semi-tensor product, and presents a number of new results and algorithms. First, using the matrix semi-tensor product, the robust graph coloring is expressed into a kind of optimization problem taking in an algebraic form of matrices, based on which an algorithm is designed to find all the most robust coloring schemes for any simple graph. Second, an equivalent problem of robust graph coloring is studied, and a necessary and sufficient condition is proposed, from which a new algorithm to find all the most robust coloring schemes is established. Third, a kind of examination timetabling is discussed by using the obtained results, and a method to design a practicable timetabling scheme is presented. Finally, the effectiveness of the results/algorithms presented in this paper is shown by two illustrative examples.     

Design of a two‐level controller for an active suspension system

The paper focuses on a control design for a vehicle suspension system in which a balance between different performance demands is achieved. The starting point of the control design is a full–car model which contains nonlinear components, i.e. the dynamics of the dampers and springs and nonlinear actuator dynamics. In order to handle the high complexity of the problem this paper proposes the design of a two‐level controller of an active suspension system. The required control force is computed by applying a high‐level controller, which is designed using a linear parameter varying (LPV) method. For the control design the model is augmented with weighting functions specified by the performance demands and the uncertainty assumptions. The actuator generating the necessary control force is modelled as a nonlinear system for which a low‐level force‐tracking controller is designed. To obtain the low‐level controller a backstepping method is proposed. As an alternative solution a feedback linearization method is also presented. The operation of the controller is illustrated through simulation examples. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

二进神经网络中汉明球的逻辑意义及一般判别方法

剖析二进神经元的逻辑意义对二进神经网络的规则提取是十分重要的，在布尔空间中，汉明球是一种线性可分的空间结构，如何从汉明球中提取出具有清晰逻辑意义的规则是二进神经网络研究的一个问题，通过对MofN规则表达形式的扩展，分析了汉明球的逻辑意义，提出了表达汉明球逻辑意义的LEM规则和GEM规则方法，并且讨论了汉明球和汉明补球的等价性，另一个重要的结果是证明了二进神经元和汉明球等价的充要条件，从而建立了判别汉明球的一般方法。     

A memetic grammar inference algorithm for language learning

An unsupervised incremental algorithm for grammar inference and its application to domain-specific language development are described. Grammatical inference is the process of learning a grammar from the set of positive and optionally negative sentences. Learning general context-free grammars is still considered a hard problem in machine learning and is not completely solved yet. The main contribution of the paper is a newly developed memetic algorithm, which is a population-based evolutionary algorithm enhanced with local search and a generalization process. The learning process is incremental since a new grammar is obtained from the current grammar and false negative samples, which are not parsed by the current grammar. Despite being incremental, the learning process is not sensitive to the order of samples. All important parts of this algorithm are explained and discussed. Finally, a case study of a domain specific language for rendering graphical objects is used to show the applicability of this approach.     

Sliding Mode Control and State Estimation for a Class of Nonlinear Singularly Perturbed Systems

This paper is concerned with the design of a controller-observer scheme for the exponential stabilization of a class of singularly perturbed nonlinear systems. The controller design uses a sliding mode technique and is divided in two phases: slow feedback control and fast feedback control so that a final composite control is obtained. Assuming that only the fast state is available and the system's output is a function of the slow state, an observer design is presented. A stability analysis is also made to provide sufficient conditions for the ultimate boundedness of the full order closed-loop system when the slow state is estimated by means of the observer. An application to the model of a permanent magnet stepper motor is given to show the controller-observer methodology and stability analysis.     

基于反馈Hough变换的管道点云检测和识别

管道是流程工厂的主体，其几何形状表现为圆柱体或圆台。针对现有管道检测识别方法对噪声较为敏感、检测精度不高、检测结果难以验证等问题，本文提出一种具有轴向反馈修正的三维霍夫变换方法。首先，根据八叉树划分点云空间，计算点云法向量并生成圆柱体或圆台高斯映射图，利用三维霍夫变换法估计初始轴向；然后，基于初始轴向计算圆柱体横截面或圆台投影轮廓，并建立轴向优化目标函数，通过迭代优化获得最终的轴向；最后通过霍夫变换法拟合圆柱体或圆台轴心位置并计算半径值。实验结果表明，该方法可有效提高管道轴向、半径等参数的估算准确度，同时，本文提出的优化目标函数也为检测结果提供了一种新的评价方法。     

Reachability and stabilization of discrete-time affine systems with disturbances

This paper studies the fundamental problems: whether an affine system affected by additive disturbances is robustly transferable from a source set (simplex) to a target set (polytope) and whether it is robustly stabilizable with its state constrained in a simplex. First, a necessary and sufficient condition is derived for the existence of affine feedback control that solves the robust reachability problem. Further investigation is provided for two situations relying on whether the union of the source set and the target set is convex or non-convex. For the former one, a necessary and sufficient condition is obtained in the form of linear inequalities, while for the latter, several computationally feasible sufficient conditions are found. Second, we show that robust stabilization subject to a state constraint is equivalent to find a feasible solution to a linear equation. Once it is known that either of the problems has a solution by checking the derived conditions, design of control laws is then straightforward.