Intelligent Engineering Systems and Computational Cybernetics

The paper describes an on-line trajectory time-scaling control algorithm for wheeled mobile robots. To reduce tracking errors the controller modifies the velocity profile of the reference trajectory according to the closed loop behavior of the robot. The geometry of the reference trajectory is unchanged, only the time distribution varies during the motion. We give a control algorithm which uses time-scaled reference and a feedback calculated from the linearized error dynamics. The closed loop behavior is also studied together with the controllability of the linearized error dynamics.

This paper gives the fuzzy reactive control of a wheeled mobile robot motion in an unknown environment with obstacles. The model of the vehicle has two driving wheels and the angular velocities of the two wheels are independently controlled. When the vehicle is moving towards the target and the sensors detect an obstacle, an avoiding strategy is necessary. We proposed a fuzzy reactive navigation strategy of collision-free motion in an unknown environment with obstacles. First, the vehicle kinematics constraints and kinematics model are analyzed. Then the fuzzy reactive control of a wheeled mobile robot motion in an unknown environment with obstacles is proposed. Output of the fuzzy controller is the angular speed difference between the left and right wheels (wheel angular speed correction) of the vehicle. The simulation results show the effectiveness and the validity of the obstacle avoidance behavior in an unknown environment of the proposed fuzzy control strategy.

This paper presents a general overview of education of robot hardware architecture and software. A well supplied microcontroller laboratory is needed for mobile robot development. The paper examines the software and hardware used for microcontroller/robotics laboratory. The work presents a project to enhance the microcontroller/robotics education of informatics and electronics engineering students using local and remote microcontroller/ microprocessor laboratory. Solutions over the internet open the possibilities for the distance learning.

An acceleration based force-impedance controller is presented in this paper. The proposed control strategy is applied to a six-dof parallel robotic mini-manipulator: the Robotic Controlled Impedance Device (RCID).

The control strategy involves three cascade controllers: an inner acceleration controller, built as a set of six Single-Input-Single-Output (SISO) acceleration controllers (one per manipulator axis), an impedance task-space controller, and an outer force controller. The proposed control strategy enables two kinds of manipulator behaviour: force limited impedance control and position limited force control. The type of behaviour only depends on the chosen manipulator trajectories.

The RCID may be used as a force-impedance controlled auxiliary device, coupled in series with a position controlled industrial robot, or as a stand-alone force feedback display, that may be used as a master manipulator in master-slave telemanipulated systems or as a haptic device interacting with virtual environments.

Experimental results of the RCID used as an auxiliary device working coupled to an industrial manipulator are presented.

This paper analyzes the signals captured during impacts and vibrations of a mechanical manipulator. In order to acquire and study the signals an experimental setup is implemented. The signals are treated through signal processing tools such as the fast Fourier transform and the short time Fourier transform. The results show that the Fourier spectrum of several signals presents a non integer behavior. The experimental study provides valuable results that can assist in the design of a control system to deal with the unwanted effects of vibrations.

Membrane proteins (MPs) are large set of biological macromolecules that play a fundamental role in physiology and pathophysiology for survival. From a pharma-economical perspective, though it is the fact that MPs constitute ˜75% of possible targets for novel drugs but MPs are one of the most understudied groups of proteins in biochemical research. This is mainly because of the technical difficulties of obtaining structural information about trans-membrane regions (these are small sequences that crossways the bilayer lipid membrane). It is quite useful to predict the location of transmembrane segments down the sequence, since these are the elementary structural building blocks defining their topology. There have been several attempts over the last 20 years to develop tools for predicting membrane-spanning regions but current tools are far away from achieving a considerable reliability in prediction. This study aims to exploit the knowledge and current understanding in the field of artificial neural networks (ANNs) in particular data representation through the development of a system to identify and predict membrane-spanning regions by analysing primary amino acids sequence. In this paper we present a novel neural network (NNs) architecture and algorithms for predicting membrane spanning regions from primary amino acids sequences by using their preference parameters.

In this article, the structure and design procedure of a new time-invariant complex-valued multi-channel non-linear microstatistic filter (C-M-CMF) will be proposed. The C-M-CMFs belong to a group of minimum mean-square estimators based on the estimation of desired signals by using a linear combination of vector elements obtained by a threshold decomposition of the input signals of the filter. The C-M-CMF represents a modification of multi-channel real-valued conventional microstatistic filter (M-CMF) originally developed in [4, 10, 11] for the purpose of design of a non-linear multi-user receiver for code division multiple access transmission systems (CDMA). The C-M-CMF theory developed in this paper can be applied for the design of new complex-valued receivers for multi-carrier code division multiple access transmission systems (MC-CDMA).

The use of ontologies is today widely spread across many different domains. The main effort today is, with the development of Semantic Web, to make them available across the Internet community with the purpose of reuse. The legal domain has also been explored concerning ontologies, both on the general as on the sub-domain level. In this paper are explored problems of formal ontology development regarding areas in specific legislation acts that are understated or unequally described across the act — popularly said: loopholes in the law. An example of such a problematic act is shown. For ontology implementation, a well-known tool, Protégé, is used. The ontology is made in formal way, using PAL — Protégé Axiom Language, for expressing constraints, where needed. Ontology is evaluated using known evaluation methods.

A class of fuzzy process models can be subjected to linguistic inversion, a technique that has great potential for use in process control but the inversion technique itself needs refinement before it can be regarded as a viable controller design method. The key elements of the procedure that is under observation here are the reliability-oriented modelling algorithm and the automatic inversion technique. When the developed approach is applied to the fed-batch fermentation benchmark, good control performance is observed, confirming the validity of our assumptions. It should be noted, however, that the approach has its natural limits because it fails to explore the solution space exhaustively.

Document clustering is an important and widely researched part of information retrieval. It aims to assign natural language document to various categories based on some criteria. In this case, this criteria is the topic of the document, which means, that the goal is to identify the topic of documents and group the similar ones together. As there are many clustering methods and noise filtering techniques to support this procedure, this paper focuses on the composition of such transformations and on the comparison of the configurations built from a subset of these transformations techniques as tiles of the whole procedure. Altogether five tile methods (term filtering, frequency quantizing, singular value decomposition (SVD), term clustering (for double clustering) and document clustering of course) are used. These are compared based on the maximal achieved F-measure and time consumption to find the best composition.

The paper addresses problems of data and knowledge reasoning in the domain of Semantic Web. The objective of this research was to explore object-oriented logic programming languages in the light of Semantic Web concept. It will be shown that logical formalisms integrating the deductive component and the object-oriented approach and featuring the second-order syntax and the first-order semantics provide an adequate Web data representation and reasoning. The paper describes elements relevant for Web data representation and integration for chosen data domain.

The paper deals with knowledge transformation process on the background of geospatial data modelling and discusses the possibilities of the context use as a reflection of the system of understanding. The problem of the relation to the decision support system is addressed and GIS as a tool dealing with all phases of knowledge structure. The paper shows that with the development of the Web services architecture there is a clear trend towards GIS becoming more open, robust and interoperable.

Ontologies that explicitly identify objects, properties, and relationships in specific domains are essential for collaboration that involves sharing of data, knowledge or resources. A communications network modelling ontology (CNMO) has been designed to represent a network model as well as aspects related to its development and actual network operation. Network nodes/sites, link, traffic sources, protocols as well as aspects of the modeling/simulation scenario and operational aspects are defined with their formal representation. A CNMO may be beneficial for various network design/simulation/research communities due to the uniform representation of network models. This ontology is designed using terminology and concepts from various network modeling, simulation and topology generation tools.

Machine condition monitoring is gaining importance in industry due to the need to increase machine reliability and decrease the possible loss of production due to machine breakdown. Often the data available to build a condition monitoring system does not fully represent the system. It is also often common that the data becomes available in small batches over a period of time. Hence, it is important to build a system that is able to accommodate new data set as it becomes available without compromising the performance of the previously learned data. Two incremental learning algorithm are implemented, the first method uses Fuzzy ARTMAP (FAM) algorithm and the second uses Learn++ algorithm. Experimental results show that both methods can accommodate both new data and new classes.

In this research, statistical analyses of Web traffic were carried out based on the Empirical Distribution Function (EDF) test. Several probability distributions, such as Pareto (simple), extreme value, Weibull (three parameters), exponential, logistic and Pareto (generalized) have been chosen to fit the experimental traffic data (traces), which show an analytical indication of traffic behaviour. The issues of traffic characterisation and performance shown by these models are discussed in terms of the heavy tailedness and fitness of the curves. The aim of the research is to find a suitable analytical, method which can characterise the Web traffic.

Capturing the meaning of internet search queries can significantly improve the effectiveness of search retrieval. Users often have problem to find relevant answer to their queries, particularly, when the posted query is ambiguous. The orientation of the user can be greatly facilitated, if answers are grouped into topics of a fixed subject taxonomy. In this manner, the original problem can be transformed to the labelling of queries — and consequently, the answers — with the topic names. Thus the original problem is transformed into a classification set-up. This paper introduces our Ferrety algorithm that performs topic assignment, which also works when there is no directly available training data that describes the semantics of the subject taxonomy. The approach is presented via the example of ACM KDD Cup 2005 problem, where Ferrety was awarded for precision and creativity.

Most scheduling problems are NP-hard, the time required to solve the problem optimally increases exponentially with the size of the problem. Scheduling problems have important applications, and a number of heuristic algorithms have been proposed to determine relatively good solutions in polynomial time. Recently, genetic algorithms (GA) are successfully used to solve scheduling problems, as shown by the growing numbers of papers. GA are known as one of the most efficient algorithms for solving scheduling problems. But, when a GA is applied to scheduling problems various crossovers and mutations operators can be applicable. This paper presents and examines a new concept of genetic operators for scheduling problems. A software tool called hybrid and flexible genetic algorithm (HybFlexGA) was developed to examine the performance of various crossover and mutation operators by computing simulations of job scheduling problems.

The purpose of this paper is to formulate truth-value assignment to self-referential sentences via Zadeh's truth qualification principle and to present new methods to assign truth-values to them. Therefore, based on the truth qualification process, a new interpretation of possibilities and truth-values is suggested by means of type-2 fuzzy sets and then, the qualification process is modified such that it results in type-2 fuzzy sets. Finally, an idea of a comprehensive theory of type-2 fuzzy possibility is proposed. This approach may be unified with Zadeh's Generalized Theory of Uncertainty (GTU) in the future.

This paper reports the modeling and control of harmonic drives in differential gearing configuration where none of its shafts is fixed. This configuration makes it possible to solve a control problem where one applies two actuators in order to carry out simultaneous position and torque control on two different axes.

An inverted pendulum represents an unstable system which is excellent for demonstrating the use of feedback control with different kinds of control strategies. In this work state feedback of the inverted pendulum is examined. First a pole placement algorithm is explored. After that artificial intelligence (AI) methods are investigated to better cope with the nonlinearities of the physical model. The technique used is based on a hybrid system combining a neural network (NN) with a genetic algorithm (GA). The NN controller is trained by the GA against the behaviour of the physical model. The results of the training process show that the chromosome population tends to station at a suboptimal level, and that changes in the environmental parameters have to take place to reach a new optimal level. By systematically changing these parameters the NN controller will gradually adapt to the pendulum behaviour.

Fractional calculus (FC) is widely used in most areas of science and engineering, being recognized its ability to yield a superior modeling and control in many dynamical systems. In this perspective, this article illustrates two applications of FC in the area of control systems. Firstly, is presented a methodology of tuning PID controllers that gives closed-loop systems robust to gain variations. After, a fractional-order PID controller is proposed for the control of an hexapod robot with three dof legs. In both cases, it is demonstrated the system's superior performance by using the FC concepts.

This paper studies the describing function (DF) of systems consisting in a mass subjected to nonlinear friction. The friction force is composed in three components namely, the viscous, the Coulomb and the static forces. The system dynamics is analyzed in the DF perspective revealing a fractional-order behaviour. The reliability of the DF method is evaluated through the signal harmonic content and the limit cycle prediction.

Software compensation of geometric errors in coordinate measuring is hot subject because it results the decrease of manufacturing costs. The paper gives a summary of the results and achievements of earlier works on the subject. In order to improve these results a method is adapted to capture simultaneously the new coordinate frames in order use exact transformation values at discrete points of the measuring volume. The interpolation techniques published in the literature have the draw back that they could not maintain the orthogonality of the rotational part of the transformation matrices. The paper gives a technique, based on quaternions, which avoid this problem and leads to better results.

As a paradigm of strongly coupled non-linear multi-variable dynamic systems the mathematical model of the free-radical polymerization of

methyl-metachrylate

with

azobis (isobutyro-nitrile)

as an initiator and

toluene

as a solvent taking place in a jacketed Continuous Stirred Tank Reactor (CSTR) is considered. In the adaptive control of this system only a single input variable is used as the control signal (

the process input, i.e. dimensionless volumetric flow rate of the initiator

), and a single output variable is observed (

the process output, i.e. the number-average molecular weight of the polymer

). Simulation examples illustrate that on the basis of a very rough and primitive model consisting of two scalar variables various fixed-point transformations based convergent iterations result in a novel, sophisticated adaptive control.

This article investigates what kind of web services is the most effective for intelligent systems. We present a new method of web services development that allows the execution of client-defined scripts on the server side. Then we demonstrate the new system architecture and features implemented as an ontology server for the CancerGrid project. The authors believe that there will be broad applicability of the proposed method for future web services.

The advent of terrorist threats has heightened local, regional, and national governments' interest in emergency response and disaster preparedness. The threat of natural disasters also challenges emergency responders to act swiftly and in a coordinated fashion. When a disaster occurs, an ad hoc coalition of pre-planned groups usually forms to respond to the incident. History has shown that these “system of systems” do not interoperate very well. Communications between fire, police and rescue components either do not work or are inefficient. Government agencies, non-governmental organizations (NGOs), and private industry use a wide array of software platforms for managing data about emergency conditions, resources and response activities. Most of these are stand-alone systems with very limited capability for data sharing with other agencies or other levels of government. Information technology advances have facilitated the movement towards an integrated and coordinated approach to emergency management. Other communication mechanisms, such as video teleconferencing, digital television and radio broadcasting, are being utilized to combat the challenges of emergency information exchange. Recent disasters, such as Hurricane Katrina and the tsunami in Indonesia, have illuminated the weaknesses in emergency response. This paper will discuss the need for defining requirements for components of ad hoc coalitions which are formed to respond to disasters. A goal of our effort was to develop a proof of concept that applying information modeling to the business processes used to protect and mitigate potential loss of an enterprise was feasible. These activities would be modeled both pre- and post-incident.

When a user or a designer tries to describe a system or a service provided by that system, then he/she faces some confusion in choosing the right qualitative and/or quantitative performance concepts. In fact, many concepts are used by many research and study groups in different ways; yet these same concepts are inconsistently used. Therefore, these qualitative/quantitative characteristic keep growing without limits and need to be clarified. This paper provides clear insights to the general problem of understanding these concepts and their relationship by integrating them into a one structure. It lays the foundation for achieving a unified design model for these characteristics, which will formulate the basic issues to develop unified quantitative approaches, tools, or evaluation methods. The expected outcomes would benefit many different entities in enhancing the design or optimizing it for achieving better systems and networks.

Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophisticated) agents interacting locally with their environment cause coherent functional global patterns to emerge. Particle swarm optimization (PSO) is a form of SI, and a population-based search algorithm that is initialized with a population of random solutions, called particles. These particles are flying through hyperspace and have two essential reasoning capabilities: their memory of their own best position and knowledge of the swarm's best position. In a PSO scheme each particle flies through the search space with a velocity that is adjusted dynamically according with its historical behavior. Therefore, the particles have a tendency to fly towards the best search area along the search process. This work proposes a PSO based algorithm for logic circuit synthesis. The results show the statistical characteristics of this algorithm with respect to number of generations required to achieve the solutions. It is also presented a comparison with other two Evolutionary Algorithms, namely Genetic and Memetic Algorithms.

The most prominent systems theories from the 20th century are reviewed in this chapter and the arguments of complex system theorists is supported who use the term “plec-tics” instead of the overused and ambiguous “systems science” and “systems theory”. It is claimed that the measurement of complex systems cannot be separated from their modelling as the boundaries between the specific steps of the scientific method are necessarily blurred. A critical and extended interpretation of the complex system modelling method is provided and the importance of discipline-specific paradigms and their systematic interdisciplinary transfer is proposed.

The spatial relational PLA-Model is very handy to store two-connected planar graphs, but in its original form it is not capable at all to store any other important classes of planar graphs. In this paper we enhance the model and describe a method to represent trees. The approach is based on Halin graphs, that are planar graphs of minimum degree 3 from which a tree is obtained when the boundary edges of the infinite region are removed. We show how Halin graphs can be identified from the model, and how trees can be represented as virtual Halin graphs in order to store them without major alteration of the original PLA-Model.

In this paper, we consider a Stackelberg duopoly competition with differentiated goods, linear and symmetric demand and with unknown costs. In our model, the two firms play a non-cooperative game with two stages: in a first stage, firm

F

1

chooses the quantity,

q

1

, that is going to produce; in the second stage, firm

F

2

observes the quantity

q

1

produced by firm

F

1

and chooses its own quantity

q

2

. Firms choose their output levels in order to maximise their profits. We suppose that each firm has two different technologies, and uses one of them following a certain probability distribution. The use of either one or the other technology affects the unitary production cost. We show that there is exactly one perfect Bayesian equilibrium for this game. We analyse the variations of the expected profits with the parameters of the model, namely with the parameters of the probability distributions, and with the parameters of the demand and differentiation.

The differentiation of non-integer order has its origin in the seventeenth century, but only in the last two decades appeared the first applications in the area of control theory. In this paper we consider the study of a heat diffusion system based on the application of the fractional calculus concepts. In this perspective, several control methodologies are investigated namely the fractional PID and the Smith predictor. Extensive simulations are presented assessing the performance of the proposed fractional-order algorithms.

Advancements in product development have reached full integration of engineering activities and processes in product lifecycle management (PLM) systems. PLM systems are based on high-level modeling, simulation and data management. Despite significant development of modeling in PLM systems, a strong demand was recognized for improved decision assistance in product development. Decision assistance can be improved by application of methods from the area of computer intelligence. In order for a product development company to stay competitive, it is important for its modeling system to be relied on local even personal knowledge. The authors analyzed current PLM systems for shortcomings and possibilities for extended intelligence at decision-making during product development. They propose methods in order to increase suitability of current modeling systems to accommodate knowledge based IT at definition of sets of parameters of modeled objects and in the management of frequent changes of modeled objects. In the center of the proposed methodology, constrained parameters act as restricting factors at definition and modification of parameters of associative engineering objects. Paper starts with an outlook to modeling in current engineering systems and preliminary results by the authors. Following this, groups of essential information as handled by he proposed modeling are summarized and procedures for processing of that groups of information are detailed. Next, management of chains of changes along chains of associa-tive product objects and a new style of decision assistance in modeling systems are explained. Changes are created or verified by behavior analysis. Finally, behavior analysis, human intent combination, product data view creation, and change management are discussed as the proposed integrated and coordinated methodology for enhanced support of decision-making in product development.

We consider a Stackelberg model with demand uncertainty, only for the first mover. We study the advantages of leadership and flexibility with the variation of the demand uncertainty. Liu proved for demand uncertainty parameter greater than three that the follower firm can have an advantage with respect to the leading firm for some realizations of the demand intercept. Here, we prove that for demand uncertainty parameter less than three the leading firm is always in advantage.

We present deterministic dynamics on the production costs of Cournot competitions, based on perfect Nash equilibria of nonlinear R&D investment strategies to reduce the production costs of the firms at every period of the game. We analyse the effects that the R&D investment strategies can have in the profits of the firms along the time. We show that small changes in the initial production costs or small changes in the parameters that determine the efficiency of the R&D programs or of the firms can produce strong economic effects in the long run of the profits of the firms.

We present stochastic dynamics on the production costs of Cournot competitions, based on perfect Nash equilibria of nonlinear R&D investment strategies to reduce the production costs of the firms at every period of the game. We analyse the effects that the R&D investment strategies can have in the profits of the firms along the time. We observe that, in certain cases, the uncertainty can improve the effects of the R&D strategies in the profits of the firms due to the non-linearity of the profit functions and also of the R&D parameters.

Due to limitations of classical weighted average aggregation operators, there is an increase usage of fuzzy integrals, like the Sugeno and Choquet integrals, as alternative aggregation operators. However, their applicability has been threatened by the crux of determining the fuzzy measures in real problems. One way to determine these measures is by using learning data and optimizing the parameters. In this paper we made a comparative study of two well known optimization algorithms, Genetic Algorithm and Gradient Descent to determine fuzzy measures. Two illustrative cases are used to compare the algorithms and assess their performance.

Medium Access Control (MAC) is an important part of wireless telecommunication systems. The main goal of a MAC protocol is to provide the best usage of the common resources for the users. One of these resources is typically the communication channel. By quantum informatics and computation—that gain more and more attention—some calculations and algorithms may become more efficient. The possible implementation of a quantum based system would lead us to great benefits, by applying it to an already existing problem. In this paper we give a model for medium access control via quantum methods.

Both humans and machines exhibit strengths and weaknesses that can be enhanced by merging the two entities. This research aims to provide a broader understanding of how closer interactions between these two entities can facilitate more optimal goal-directed performance through the use of artificial extensions of the human body. Such extensions may assist us in adapting to and manipulating our environments in a more effective way than any system known today. To demonstrate this concept, we have developed a simulation where a semi interactive virtual spider can be navigated through an environment consisting of several obstacles and a virtual predator capable of killing the spider. The virtual spider can be navigated through the use of three different control systems that can be used to assist in optimising overall goal directed performance. The first two control systems use, an onscreen button interface and a touch sensor, respectively to facilitate human navigation of the spider. The third control system is an autonomous navigation system through the use of machine intelligence embedded in the spider. This system enables the spider to navigate and react to changes in its local environment. The results of this study indicate that machines should be allowed to override human control in order to maximise the benefits of collaboration between man and machine. This research further indicates that the development of strong machine intelligence, sensor systems that engage all human senses, extra sensory input systems, physical remote manipulators, multiple intelligent extensions of the human body, as well as a tighter symbiosis between man and machine, can support an upgrade of the human form.