Imre J. Rudas

On continuous triangular norms that are migrative

In this paper we completely describe all continuous migrative triangular norms. Since the migrative property excludes both idempotent and nilpotent classes, the characterization and construction is carried out by solving a functional equation for additive generators of strict t-norms. We also study cases when the construction results in a smooth generator.

Entropy-based operations on fuzzy sets

By using a fuzzy entropy approach, three sets of new generalized operators are presented. After a general discussion on fuzzy entropy, the concept of an elementary entropy function of a fuzzy set is introduced. Using this mapping, the generalized intersections and unions are defined as mappings that assign the least and the most fuzzy membership grade to each of the elements of the domain of the operators, respectively. It is shown that these operators can be constructed from the conventional min and max operations. Next, two modified sets of operations are introduced. The second part of the paper investigates the applicability of the new operators in fuzzy logic controllers. Simulations have been carried out so as to determine the effects of the operators on the performance of the fuzzy controllers. It is concluded that the first set of operators does not provide stable control, but the performance of the fuzzy controller can be improved by using the modified operations for a class of plants.

New types of generalized operations

New methods for constructing generalized triangular operators, using a minimum and maximum fuzziness approach are outlined. Based on the entropy of a fuzzy subset, defined by using the equilibrium of the generalized fuzzy complement, the concept of elementary entropy function and its generalizations are introduced. These functions assign a value to each element of a fuzzy subset that characterizes its degree of fuzziness. It is shown that these functions can be used to construct the entropy of a fuzzy subset. Using this mapping, the generalized intersections and unions are defined as mappings, that assign the least and the most fuzzy membership grade to each of the elements of the operators’ domain, respectively. Next further classes of new generalized T-operators are introduced, also defined as minimum and maximum entropy operations. It is shown that they are commutative semigroup operations on [0,1] with identity elements but they are not monotonic. Simulations have been carried out so as to determine the effects of these new operators on the performance of the fuzzy controllers. It is concluded that the performance of the fuzzy controller can be improved by using some sets of generalized T-operations for a class of plants.

Intelligent Engineering Systems and Computational Cybernetics

Engineering practice often has to deal with complex systems of multiple variable and multiple parameter models almost always with strong non-linear coupling. The conventional analytical techniques-based approaches for describing and predicting the behaviour of such systems in many cases are doomed to failure from the outset, even in the phase of the construction of a more or less appropriate mathematical model. These approaches normally are too categorical in the sense that in the name of modelling accuracy they try to describe all the structural details of the real physical system to be modelled. This can significantly increase the intricacy of the model and may result in a enormous computational burden without achieving considerable improvement of the solution. The best paradigm exemplifying this situation may be the classic perturbation theory: the less significant the achievable correction, the more work has to be invested to obtain it. A further important component of machine intelligence is a kind of structural uniformity giving room and possibility to model arbitrary particular details a priori not specified and unknown. This idea is similar to the ready-to-wear industry, which introduced products, which can be slightly modified later on in contrast to tailor-made creations aiming at maximum accuracy from the beginning. These subsequent corrections can be carried out by machines automatically. This learning ability is a key element of machine intelligence. The past decade confirmed that the view of typical components of the present soft computing as fuzzy logic, neural computing, evolutionary computation and probabilistic reasoning are of complementary nature and that the best results can be applied by their combined application. Today, the two complementary branches of Machine Intelligence, that is, Artificial Intelligence and Computational Intelligence serve as the basis of Intelligent Engineering Systems. The huge number of scientific results published in Journal and conference proceedings worldwide substantiates this statement. The present book contains several articles taking different viewpoints in the field of intelligent systems.

Virtual intelligent space for engineers

Computer descriptions of engineering objects such as elements and structures of products, results of tests and analyses, and engineering processes for design, analysis, and manufacturing of products have been integrated. The resulted complex product models support lifecycle management of product data. Engineering utilizes advanced characteristics of modeling software such as analysis of behaviors, adaptive actions for controlled modifications of engineering objects, selection of optimal sets of parameters, etc. The next step of integration is hoped to establish virtual intelligent space where all outside and inside effects are reacted by high level model to simulate a physical intelligent space. The authors conceptualized a virtual intelligent space as a well-organized structure of descriptions and behavior definitions for engineering objects that identified in a physical space. Sensor signals in physical intelligent space are replaced by received change information, processing of change information is done by behavior analysis, and actuators are replaced by adaptive action generators. In this paper, a new virtual intelligent space idea is introduced for virtual engineering systems. Following this, methods for including intelligence into these systems are explained and detailed. Finally, characteristics of virtual intelligent space for engineering are briefed.

Novel Adaptive Control of Partially Modeled Dynamic Systems

The basic components of Soft Computing were almost completely developed by the sixties. In our days SC means either separate or integrated application of Neural Networks (NN) and Fuzzy Systems (FS) enhanced with high parallelism of operation and supported by several deterministic, stochastic or combined parameter-tuning methods (learning). The main advantage of using FS is evading the development of intricate analytical system models.

Hierarchical control of a distributed solar collector field

This article presents a hierarchical control structure aimed at optimizing the electricity production process in solar power plants with distributed collectors. In these systems, a fluid is heated using the energy provided by the solar irradiation until a desired outlet temperature range is achieved, despite of the effect of disturbances (mainly radiation and inlet temperature),using as manipulated variable the fluid flow. The heated fluid is then used for feeding a heat exchanger where steam is produced for electricity generation using a turbine. Nonlinear models are used in the design of the different layers of the control architecture.

Comparing wireless sensor network routing protocols

Selecting a routing protocol for a wireless sensor network depends on various factors like the network lifetime, success rate and the number of nodes in the network. This paper compares four popular routing protocols used in wireless sensor networks. The experimental setup is described, after which the various protocols are compared and evaluated.

Application of part manufacturing process model in virtual manufacturing

The paper introduces a research to integrate manufacturing process modeling in virtual manufacturing. This requires development of manufacturing process modeling as a tool for evaluation of manufacturability of mechanical products. The authors apply for this purpose a manufacturing process modeling method that makes it possible to create a more or less generic process model for clusters of manufacturing tasks. Integration of this modeling method in a comprehensive product model is an another purpose of the research. Using evaluation of this process model, manufacturability of parts is assessed on the basis of part model information. Production environment, production planning and cost data are used for this assessment. Manufacturing process model entities are represented by Petri nets. This formalism has proved to be a versatile virtual manufacturing tool in manufacturing process planning and manufacturing environment design. The authors offer a procedure for evaluation of the applied process model. Feasibility and resource requirements of the manufacturing are revealed. The paper starts with an introduction to the applied concept in virtual manufacturing. Then the applied process model is outlined. Following this, concept, method and characteristics of the manufacturability analysis as well as some solutions for problems emerging during evaluation of the model in close connection with changes in design and production environment are detailed. Finally, impact of the proposed manufacturing process model as an integrated element in a comprehensive virtual manufacturing concept is explained.

New trends in information aggregation

Information aggregation is one of the key issues in the development of intelligent systems, like neural networks, neuro-fuzzy systems, fuzzy knowledge based systems, vision and decision making systems, etc. Fuzzy set theory provides a host of attractive aggregation operators for integrating the membership values representing uncertain information. The variety of these operators might be confusing and make it difficult to decide which one to use in a specific model or situation. The tutorial gives a survey of the existing aggregation connectives starting from the classical Zadehian-operators, through the theory of t-operators, till the most up-to-date operators, containing the results of the author and his colleagues on entropy and evolutionary operators.