Search results for "Neuro-fuzzy"
showing 10 items of 19 documents
Inverse kinematics of a 7 DOF manipulator using Adaptive Neuro-Fuzzy Inference Systems
2012
This paper was carried out objectively to explore and describe the inverse kinematics solutions of an anthropomorphic redundant robotic structure with seven degrees of freedom and human like workspace. Traditional inverse kinematics methods can have an unacceptably slow pace for the today's extremely redundant systems. The presented method uses the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) editor and the Fuzzy Logic toolbox from MATLAB® which allow the investigation of various kinematical suitable solutions. ANFIS supports the determination of one degree of freedom, remaining therefore only six undetermined degrees. For better understanding of the simulations a CAD model that mimics th…
Type-2 Fuzzy Control of a Bioreactor
2009
Abstract—In this paper the control of a bioprocess using an adaptive type-2 fuzzy logic controller is proposed. The process is concerned with the aerobic alcoholic fermentation for the growth of Saccharomyces Cerevisiae a n d i s characterized by nonlinearity and parameter uncertainty. Three type-2 fuzzy controllers heve been developed and tested by simulation: a simple type-2 fuzzy logic controller with 49 rules; a type-2 fuzzyneuro- predictive controller (T2FNPC); a t y p e -2 selftuning fuzzy controller ( T2STFC). The T2FNPC combines the capability of the type-2 fuzzy logic to handle uncertainties, with the ability of predictive control to predict future plant performance making use of a…
A very brief history of soft computing: Fuzzy Sets, artificial Neural Networks and Evolutionary Computation
2013
This paper gives a brief presentation of history of Soft Computing considered as a mix of three scientific disciplines that arose in the mid of the 20th century: Fuzzy Sets and Systems, Neural Networks, and Evolutionary Computation. The paper shows the genesis and the historical development of the three disciplines and also their meeting in a coalition in the 1990s.
A Fuzzy Discrete Event Simulator for Fuzzy Production Environment Analysis
1998
Abstract Discrete Event Simulation is a powerful tool to help production managers in planning manufacturing systems. The necessity to rapid react to market conditions is pushing production planners to process requirements and information affected by vagueness. Vagueness is related with event definition, therefore it is not manageable through statistical tools, but more properly by using fuzzy mathematics. Production situations where uncertainty takes body in term of vagueness are referred as Fuzzy Production Environments. Classical Discrete Event simulators are not suitable to deal with fuzzy variables, therefore they cannot be used to model Fuzzy Production Environments. This paper aims to…
A genetic integrated fuzzy classifier
2005
This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells. The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.
Fuzzy Classifier Based on Fuzzy Decision Tree
2007
A popular method for making a fuzzy decision tree for classification is Fuzzy ID3 algorithm. We introduce a new approach that uses cumulative information estimations of initial data. Based on these estimations we propose a new greedy version of fuzzy ID3 algorithm to be used to generate understandable fuzzy classification rules. The goal is to find a sequence of rules that causes near minimal classification costs.
Fuzzy Discrete Event Simulation for Fuzzy Production Systems Analysis
1998
Abstract Fuzzy production systems are characterised by vagueness in data and requirements that very often cannot be reduced to stochastic models. Therefore, such production systems cannot be analysed by using classical techniques such as Queue Theory or Discrete Simulation Analysis. On the other hand the great diffusion of Fuzzy Production environments in small and medium enterprises claims for the development of new analysis tools. This paper proposes a new approach to Discrete Event Simulation able to treat with fuzzy variables. A new methodology has been proposed to process fuzzy information within discrete event simulation and a prototype of a Fuzzy Discrete Event Simulator has been dev…
Studies regarding the use of a neuro-fuzzy mathematical model in order to determine the technological parameters of the polyethylene pipes butt weldi…
2017
The paper analyzes the possibility to use a neuro-fuzzy type mathematical model, with the final goal of establishing the welding parameters for new types and dimensions of pipes and fittings. Anticipating the developing dynamic of polyethylene-made elements, especially pipes and fittings, starting from the current situation when already a wide range of pipes and fittings with different wall thicknesses and nominal working pressures is produced and commercialized, and taking into account also new development, it was considered necessary to find out the welding parameters for any new pipe type and dimension. The usage of existing welding equipment for new pipe dimensions is impossible without…
Controller Design Under Fuzzy Pole-Placement Specifications: An Interval Arithmetic Approach
2006
This paper discusses fuzzy specifications for robust controller design, as a way to define different specification levels for different plants in a family and allow the control of performance degradation. Controller synthesis will be understood as mapping a fuzzy plant onto a desired fuzzy set of closed-loop specifications. In this context, a fuzzy plant is considered as a possibility distribution on a given plant space. In particular, pole placement in linear plants with fuzzy parametric uncertainty is discussed, although the basic idea is general and could be applied to other settings. In the case under consideration, the controller coefficients are the solution of a fuzzy linear system o…
Viability of infeasible portfolio selection problems: A fuzzy approach
2002
Abstract This paper deals with fuzzy optimization schemes for managing a portfolio in the framework of risk–return trade-off. Different models coexist to select the best portfolio according to their respective objective functions and many of them are linearly constrained. We are concerned with the infeasible instances of such models. This infeasibility, usually provoked by the conflict between the desired return and the diversification requirements proposed by the investor, can be satisfactorily avoided by using fuzzy linear programming techniques. We propose an algorithm to repair infeasibility and we illustrate its performance on a numerical example.