An optimal gas-fired heating system

Utilizing a prescribed system configuration, this paper discusses the mathematical models of the system components used and formulates a method for controlling a domestic heating system in accordance to a prescribed criterion. The optimal problem treated is one of reducing the room temperature deviation from a prescribed reference value to zero, while at the same time minimizing the value of some predetermined performance or cost functional J. The development proceeds in essentially five steps.

1. (a) The development of the mathematical models for each of the elements of the heating system;

2. (b) Combining the mathematical models into a form which is suitable for the application of optimization techniques;

3. (c) Defining an optimization criterion which incorporates the main objective for minimizing room temperature variations with respect to a prescribed reference temperature;

4. (d) Choosing the optimization technique best suited for the problem;

5. (e) Constructing an optimal control system employing the optimization technique developed.

A numerical example compares the performance of the optimal system with a system of the conventional type which can be found in many American homes.     

Database considerations in manufacturing systems integration

This paper deals with ideas that could form a basis for manufacturing integration. In recent times more attention is being paid to the idea of applying artificial intelligence (AI) techniques to manufacturing. However, very little attention is being paid to the proper use of these techniques. This research work explores three basic ideas:

1. 1. Applications of the entity-relationship approach to knowledge representation.

2. 2. The basic philosophy of expert database systems and

3. 3. Integration of manufacturing systems from the above two concepts.

The approaches for 1 and 2 are explained with actual implementation experiences, while a framework for integration is proposed from a more philosophical perspective.     

Observer-based multivariable flatness control of a cold rolling mill

The synthesis methodology developed by Kimura (1985) based on the design theory of output regulators essentially due to Wonham (1974) has been applied successfully to the flatness control system for a 6-high cold rolling mill. The system has the following remarkable features.

1. (1) The structure of the controller is simple. This makes it easy to tune the control system.

2. (2) The controller copes well with the detection time delay, and thus high performance is obtained even at a low rolling speed.

3. (3) The flatness error caused by the rolling force variation in mill acceleration and deceleration time would be kept to a minimum by the function to adjust roll bending force using the signal of rolling force.

An analysis of research topics in software engineering – 2006

This paper is the first in a new annual series whose goal is to answer the following question: what are the active research focuses within the field of software engineering? We considered 7 top journals and 7 top international conferences in software engineering and examined all the 691 papers published in these journals or presented at these conferences in 2006. Consequently, we have a number of findings.

(1) Seventy-three percent of journal papers focus on 20% of subject indexes in software engineering, including Testing and Debugging (D.2.5), Management (D.2.9), and Software/Program Verification (D.2.4).

(2) Eighty-nine percent of conference papers focus on 20% of subject indexes in software engineering, including Software/Program Verification (D.2.4), Testing and Debugging (D.2.5), and Design Tools and Techniques (D.2.2).

(3) Seventy-seven percent of journal/conference papers focus on 20% of subject indexes in software engineering, including Testing and Debugging (D.2.5), Software/Program Verification (D.2.4), and Management (D.2.9).

(4) The average number of references cited by a journal paper is about 33, whereas this number becomes around 24 for a conference paper.

Discrete warehouse problem

A discrete warehouse is a collection of two-dimensional unit-square objects (robot and obstacles), which are allowed to move horizontally and vertically along grid lines. In this paper, we consider motion planning problems in a discrete warehouse with movable obstacles. In such a setup one is allowed to move some of the obstacles in order to:

1. (1) navigate the robot between an initial and a final position of the warehouse, and

2. (2) construct a clearing (path) between two specified points.

The final positions of the obstacles are unimportant for our problems.

We consider two forms of obstacle manipulations:

1. (a) remote, when the obstacles are moved by a remote mechanism, and

2. (b) contact, when the obstacles are moved only by direct contact of the robot.

We present necessary and sufficient conditions for the existence of a motion in both cases, and propose efficient algorithms for constructing feasible motions.     

基于F-SVMs的多模型建模方法

针对全局模型难以精确描述复杂工业过程的问题,提出一种基于模糊支持向量机(F-SVMs)的多模型(F-SVMs MM)建模方法。用模糊支持向量分类算法(F-SVC)对输入数据进行预处理,得到多模型模糊隶属度;用模糊支持回归算法(F-SVR)建立多模型(MM)估计器。应用该方法对pH中和滴定过程进行建模,仿真结果表明,F-SVMs MM跟踪性能好、泛化能力强,比USOCPN方法和标准支持向量机(SVMs)方法具有更好的性能和推广能力。     

A survey of simple transfer-function derivations from high-order state-variable models

The problem of the derivation of simple transfer function models from high order state variable models is reviewed. Methods of reduction are classified according to whether they involve

1. (a) the computation of the time or frequency responses

2. (b) the derivation, as an intermediate step, of a transfer function which is the ratio of two polynomials, the denominator being of the same order as the state variable model, or

3. (c) a set of characterising functions.

Particular reduction methods considered are those based on fitting the step or frequency responses, on determining the intermediate, high order transfer function and reducing it by continued fraction expansion and on fitting the moments of the impulse response. An example illustrating these methods is given. The form of the simple model, the criteria of goodness of fit and the practical difficulties involved in the use of these methods are discussed.     

A note on the combinatorial structure of the visibility graph in simple polygons

Combinatorial structure of visibility is probably one of the most fascinating and interesting areas of engineering and computer science. The usefulness of visibility graphs in computational geometry and robotic navigation problems like motion planning, unknown-terrain learning, shortest-path planning, etc., cannot be overstressed. The visibility graph, apart from being an important data structure for storing and updating geometric information, is a valuable mathematical tool in probing and understanding the nature of shapes of polygonal and polyhedral objects. In this research we wish to initially focus our attention on a fundamental class of geometric objects. These geometric objects may be looked upon as building blocks for more complex geometric objects, and which offer an ideal balance between complexity and simplicity, namely simple polygons.

A major theme of the proposed paper is the investigation of the combinatorial structure of the visibility graph. More importantly, the goals of this paper are:

1. (i) To characterize the visibility graphs of simple polygons by obtaining necessary and sufficient conditions a graph must satisfy to qualify for the visibility graph of a simple polygon

2. (ii) To obtain hierarchical relationships between visibility graphs of simple polygons of a given number of vertices by treating them as representing simple polygons that are deformations of one another.

3. (iii) To exploit the potential of complete graphs to be natural coordinate systems for addressing the problem of reconstructing a simple polygon from visibility graph.

We intend to achieve this by defining appropriate “betweenness” relationships on points with respect to the edges of the complete graphs.     

Use of simulation in the analysis of shop floor operations

The use of computers in actual system applications is increasing with the availability of intelligent terminals on the shop floor. These terminals can be used by management as tools in the decision making process of planning shop floor operation. This paper discusses a pilot simulation study in the use of conventional Fortran-based simulation programs by shop floor management to:

1. 1. Participate in the evaluation of proposed FMS systems,

2. 2. Assess the impact of FMS acquisition on existing facilities,

3. 3. Assist in the identification of operational alternatives in “bottle neck” situations.

The pilot study employs a batch-oriented MRP system to provide daily updates of outstanding production center loadings on a monthly planning horizon. Two intelligent terminals are used to access a mini computer facility that executes the simulation models. The terminals have AT-compatible capabilities and are also used as data acquisition devices that support the numerically controlled operations within each work center.

The simulation models represent the 13 work centers of the firm and provide information about the average utilization of each work center, the number of parts in each queue and the average delay of parts in the queues. Future extensions of the models are planned to utilize the terminals' graphic animation capabilities to display the flow of production orders through the manufacturing facility.     

Impact of personality and intelligence on job satisfaction of assembly line and bench work - an industrial study

A study of the impact of machine-paced (M/P) and self-paced (S/P) work on job satisfaction of 28 female industrial assembly workers was evaluated in which M/P work was confounded with simplified work and the S/P job was confounded with enriched tasks. Results indicated the following:

1. 1. Over three-quarters of workers were more satisfied in S/P jobs, while only less than one-quarter were more satisfied in M/P jobs.

2. 2. The 16PF personality test effectively predicts (0·88 multiple correlation) the satisfaction ratios of M/P to S/P jobs.

The monadic second-order logic of graphs X: Linear orderings

Graphs are finite and handled as relational structures. We give some answers to the following general questions:

1. (1) For which classes of graphs is it possible to specify a linear ordering of the set of vertices of each graph of by fixed monadic second-order formulas?

2. (2) For which classes of graphs does there exist an extension of monadic second-order logic such that a subclass L of is recognizable if and only if it is the class of graphs in that satisfy a formula of ? (In this paper, recognizability is understood in an algebraic sense, relative to a finite set of graph operations and basic graphs that generate all graphs of .)

3. (3) For which classes of graphs is it possible to construct, in every graph of the class, and by fixed formulas of a suitable extension of monadic second-order logic, its hierarchichal structure, i.e., a finite term written with the operations and basic graphs of (2), that defines the considered graph?

Applications concern dependency graphs of partially commutative words, partial k-paths, cographs, and graphs, the modular decomposition of which uses prime graphs of bounded size.     

A global parametrization of asymptotically stable linear systems

In this paper we construct a homeomorphism from the set of p × m transfer functions of McMillan degree n onto the open subspace of asymptotically stable linear systems. This homeomorphism yields a one-to-one correspondence between

1. (i) canonical forms for state space equivalence of minimal systems and

2. (ii) canonical forms for state space equivalence of asymptotically stable minimal systems.

Implications for the topology of various sets of asymptotically stable systems are given.     

Finite element programs based on general programming systems

This article describes the advantages and inconveniences with a finite element programming system, i.e. blocks of routines already thoroughly tested, which has to be built together by a programmer to a finite element program. This program may be a tailor-made program to fit a special problem or a general purpose finite element program.

The programming system used as an example in this article consists of

1. *NORSAM—finite element programming system

2. *DASA — pre- and postprocessors

3. *ELLIB—element library

Together they form a complete set of subroutines from datageneration through the necessary routines for matrix manipulation to presentation of results, including the multilevel superelement technique.

Reference to finite element programs applying the programming system concept, is given at the end of the article. Among others, programs for buckling, elasto-plastic analysis of 3-dimensional membranes and solids, nonlinear pipeline problems, acoustic field problems and transient heat conduction in solids are developed. The multilevel superelement technique has been applied in several of these application programs.

The concept of the programming system gives undoubtedly a large saving of time and resources and has proved to be more reliable than conventional methods when developing finite element programs.     

The fuzzy weighted average within a generalized means function

The fuzzy weighted average is widely used to solve hierarchical evaluation problems, including fuzzy consideration for the operations of scoring, weighting and aggregating. Previous works considered the fuzziness of score and weight, and used the additive function to aggregate these weighted scores. This study considers the aggregation operator also as a fuzzy variable, and uses a generalized means function to fuzzify the aggregation operator within a fuzzy weighted average. In practice, the proposed model not only considers both the relative important of the criteria and its achieved performance, but also conveys the influence of the DM’s (Decision Maker’s) evaluation attitude. Thus the proposed model can flexibly reflect any DM’s evaluation attitude, such as open, neutral or rigorous. Thereby, the proposed model can make an objective evaluation that approaches a real decision making situation, and thus has the potential to be a useful management tool for improved resolution of fuzzy hierarchical evaluation problems.     

Adaptive fuzzy identification and predictive control for industrial processes

This paper proposes a method for adaptive identification and control for industrial applications. The learning of a T–S fuzzy model is performed from input/output data to approximate unknown nonlinear processes by a hierarchical genetic algorithm (HGA). The HGA approach is composed by five hierarchical levels where the following parameters of the T–S fuzzy system are learned: input variables and their respective time delays, antecedent fuzzy sets, consequent parameters, and fuzzy rules. In order to reduce the computational cost and increase the algorithm’s performance an initialization method is applied on HGA. To deal with nonlinear plants and time-varying processes, the T–S fuzzy model is adapted online to maintain the quality of the identification/control. The identification methodology is proposed for two application problems: (1) the design of data-driven soft sensors, and (2) the learning of a model for the Generalized predictive control (GPC) algorithm. The integration of the proposed adaptive identification method with the GPC results in an effective adaptive predictive fuzzy control methodology. To validate and demonstrate the performance and effectiveness of the proposed methodologies, they are applied on identification of a model for the estimation of the flour concentration in the effluent of a real-world wastewater treatment system; and on control of a simulated continuous stirred tank reactor (CSTR) and on a real experimental setup composed of two coupled DC motors. The results are presented, showing that the developed evolving T–S fuzzy model can identify the nonlinear systems satisfactorily and it can be used successfully as a prediction model of the process for the GPC controller.     

Applications of power series in computational geometry

A number of algorithms are presented for obtaining power series expansions of curves and surfaces at a point. Some results on the radius of convergence are given. Two applications of series are given:

1. • for curve tracing algorithms, where a truncated series is used to approximate the curve of intersection of two surfaces

2. • to define nth degree geometric continuity, for arbitrary

Evaluating suppliers via a multiple levels multiple criteria decision making method under fuzzy environment

Suppliers are an important component of the supply chain. Their ability and performance are what largely determine the success or failure of the supply chain. Thus the evaluation of suppliers has become a very important part of the supply chain management of a company. This paper suggests a multiple levels multiple criteria decision making (MCDM) model under fuzzy environment to evaluate and select suppliers, where a general hierarchical structure is developed to depict the relationship among parent criteria and their sub-criteria and sub-sub-criteria and so on. These criteria are classified into quantitative and qualitative ones. The ratings of alternatives versus qualitative criteria and the importance weights of all criteria in the hierarchical structure are assessed in linguistic values represented by triangular fuzzy numbers. The ranking approach of center of area is suggested to rank all the fuzzy numbers before their weighted ratings aggregation. The final evaluation values of alternatives can then be obtained through the additive weighted ratings from the last to the first level in the criteria structure. Finally a numerical example demonstrates the feasibility of the proposed model.     

A structure identification method of submodels for hierarchical fuzzy modeling using the multiple objective genetic algorithm

Fuzzy models describe nonlinear input‐output relationships with linguistic fuzzy rules. A hierarchical fuzzy modeling is promising for identification of fuzzy models of target systems that have many input variables. In the identification, (1) determination of a hierarchical structure of submodels, (2) selection of input variables of each submodel, (3) division of input and output space, (4) tuning of membership functions, and (5) determination of fuzzy inference method are carried out. This article presents a hierarchical fuzzy modeling method with an uneven division method of input space of each submodel. For selecting input variables of submodels, the multiple objective genetic algorithm (MOGA) is utilized. MOGA finds multiple models with different input variables and different numbers of fuzzy rules as compromising solutions. A human designer can choose desirable ones from these candidates. The proposed method is applied to acquisition of fuzzy rules from cyclists' pedaling data. In spite of a small number of data, the obtained model was able to give detailed suggestions to each cyclist. © 2002 Wiley Periodicals, Inc.     

最大模糊熵阈值法的快速算法

针对最大模糊熵图像阈值分割算法计算量太大的问题,文中在分析S型隶属函数特点和模糊熵性质的基础上,提出一种最大模糊熵阈值法的快速算法。该算法将最大模糊熵阈值分割算法的时间复杂度由O(L⁴)降到O(L³),同时避免优化算法易于陷入局部极值的缺陷。该快速算法可在提高算法速度的同时保证最大模糊熵阈值法的分割性能。     

Using integrated quality function deployment and theory of innovation problem solving approach for ergonomic product design

A multidisciplinary approach integrating method of identification of customer satisfaction needs (CSNs), the House of Quality (HoQ) chart of quality function deployment (QFD), theory of innovation problem solving (TRIZ) and fuzzy group decision-making theory for ergonomic product innovative design and evaluation in the early design stages was proposed. An integrated model and the approach procedures consists of four steps. In step 1, identification of CSNs is based on a data source triangulation approach, questionnaire survey, 5-point liner numeric rating scale, factor analysis, and Cronbach’s coefficient alpha statistic are utilized to guarantee that the CSNs are complete and reliable. In step 2, a correlation matrix is built to identify the critical ergonomic design areas and the key problems are established by analysis of the negative relationships obtained from interrelationship half-matrix at the roof of the HoQ. In step 3, to solve the problems, TRIZ main tools and contradiction analysis are utilized. Several innovative alternatives are generated by combining appropriate Inventive Principles of TRIZ, the critical ergonomic design areas and the ergonomic design principles. In step 4, a general and easy fuzzy group decision-making method for evaluating of the best design alternatives is presented. A case study of the integrated kitchen stove innovative design and evaluation is conducted to demonstrate the applicability of the proposed approach.