Fuzzy relational equations have been extensively studied since 1976. There are a lot of theoretical and significant application *** side of development in this field is mainly concerned with solving equations with a w...
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Fuzzy relational equations have been extensively studied since 1976. There are a lot of theoretical and significant application *** side of development in this field is mainly concerned with solving equations with a wide class of composition operators and characterization of a set of solutions. From an aplicational point of view more and more fields of applications have been reported, as for instance:fuzzy system analysis, medical diagnosis, decision-making or pattern classification.
作者：
PEDRYCZ, WDepartment of Mathematics
Delft University of Technology Julianalaan 132 BL 2628 Delft The Netherlands On leave from Department of Automatic Control & Computer Sci. Silesian Technical University 44–100 Gliwice Poland
The paper deals with some problems of decision‐making by the use of fuzzy set theory. The application of different operators from a wide class of intersection connectives makes it possible to modelize the process of ...
The paper deals with some problems of decision‐making by the use of fuzzy set theory. The application of different operators from a wide class of intersection connectives makes it possible to modelize the process of decision‐making in a very flexible manner. The method of calculation of final non‐fuzzy decision from fuzzy set of decision D is discussed in detail and the problem of the choice of a threshold level presented as appropriate to the intersection operator applied before. The notion of sensitivity of any of intersection operators discussed is introduced and considered in detail.
The optimal stochastic approximation procedure (OSAP) is applied to the parameter identification problem of distributed parameter system (DPS) driven by random disturbances and observed through noisy measurements. Thi...
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The optimal stochastic approximation procedure (OSAP) is applied to the parameter identification problem of distributed parameter system (DPS) driven by random disturbances and observed through noisy measurements. This procedure is a stochastic approximation procedure (SAP) with an optimal gain sequence and an optimal transformation on the gradient of the objective function: these optimal values accelerate the convergence rate by minimizing the mean squared parameter estimation error, under the assumption that the density functions of the system and observation noises are known, or can be easily estimated. An example of parameter identification of a stochastic parabolic DPS is simulated on the digital computer. A comparison is made among the results of the optimal, the modified, the nominal first-order, and the nominal second-order SAP. It is shown that the OSAP gives higher accuracy and faster rate of convergence as compared to the nominal SAP
The paper deals with the design problem of control algorithms in fuzzy systems described by means of fuzzy relational equations, which can be implemented in the framework of fuzzy controllers applied to control of ill...
Several methods for the identification of linear multivariable continuous-time systems from the samples of input-output data are discussed. These include three new methods proposed by the authors. The suitability of t...
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Several methods for the identification of linear multivariable continuous-time systems from the samples of input-output data are discussed. These include three new methods proposed by the authors. The suitability of these methods for estimating the parameters of the system using recursive least-squares algorithm is compared using a simulated example. The results indicate that the best results are obtained using the block pulse function method as proposed by the authors.
The fuzzy set theory established by L. A. Zadeh has started anew period in formalizing a decision-making processes in ill-defined systems where a human being (operator) is an important element in the control loop. The...
The fuzzy set theory established by L. A. Zadeh has started anew period in formalizing a decision-making processes in ill-defined systems where a human being (operator) is an important element in the control loop. The control algorithm used here is based on a generalized fuzzy version of modus ponens (compositional rule of inference) where a set of decision-making rules forming a control algorithm is given. The aim of this paper is to present some problems which may appear in the initial stage off design of a decisionmaking algorithm and discuss a method of their formulation. We introduce notions like the completeness of algorithm, interactivity and the competitivity of control rules and consider indices illustrating the presented design aspects.
This paper deals with a formal description of ill-defined processes (fuzzy systems) by the use of fuzzy relational equations. It is pointed out that fuzzy relational equations form a generalized version of the differe...
This paper deals with a formal description of ill-defined processes (fuzzy systems) by the use of fuzzy relational equations. It is pointed out that fuzzy relational equations form a generalized version of the difference equations widely considered in control theory. Some equivalence between these two kinds of description is presented. Basic problems of fuzzy systems e.g. identification, prediction, sensitivity and stability are shown and numerical algorithms are given. Indices of each method are introduced (especially the degree of fuzziness, the sensitivity index) which makes it possible to express the quality of each of them.
The principle of orthogonal collocation has, recently found, interest for the treatment ot Two Point Boundary Value Problems, (TPBVP) using the zeros of transformed Legendre polynomials as collocation points, good to ...
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The principle of orthogonal collocation has, recently found, interest for the treatment ot Two Point Boundary Value Problems, (TPBVP) using the zeros of transformed Legendre polynomials as collocation points, good to excellent accuracies can be obtained Using a small number of collocation pOints. inconstrained IPBVP haa already been examined in the, literature. The principle, is then extended to treat state variable lnequality, constrained optimal control problems. mathematical programming technique is shown to play an, Important role, In constructing the optimal traJectories. it iS shown, bv Implementing the approach to a numerical, example of an optimal control problem that accuracies can be obtained Which are, in some cases, better than those of the well known conventional approaches to solve the same problem.
The development of fuzzy sets theory introduced by Zadeh has proved that this theory may be useful in many areas of applications. Not many papers deal with the problem evaluaging the fuzziness measures of fuzzy set. I...
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The development of fuzzy sets theory introduced by Zadeh has proved that this theory may be useful in many areas of applications. Not many papers deal with the problem evaluaging the fuzziness measures of fuzzy set. In this paper it is shown that the special kind of energy measure the so called degree of fuzziness can be more useful in many practical situations of decision making. The application of energy measure as a quality index used for fuzzy control and prediction in fuzzy systems is discussed in details.
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