Search results for " fuzzy"
showing 10 items of 209 documents
Data-based modeling of vehicle crash using adaptive neural-fuzzy inference system
2014
Vehicle crashes are considered to be events that are extremely complex to be analyzed from the mathematical point of view. In order to establish a mathematical model of a vehicle crash, one needs to consider various areas of research. For this reason, to simplify the analysis and improve the modeling process, in this paper, a novel adaptive neurofuzzy inference system (ANFIS-based) approach to reconstruct kinematics of colliding vehicles is presented. A typical five-layered ANFIS structure is trained to reproduce kinematics (acceleration, velocity, and displacement) of a vehicle involved in an oblique barrier collision. Subsequently, the same ANFIS structure is applied to simulate different…
Determining the Parameters of a Sugeno Fuzzy Controller Using a Parallel Genetic Algorithm
2013
Developed in the mid 1970s, the technique based on genetic algorithms proved its usefulness in finding optimal or near optimal solutions to problems for which accurate solving strategies are either non-existent or require excessively long running time. We implemented a genetic algorithm to determine the parameters of a Sugeno fuzzy controller for the Truck Backer-Upper problem (This problem is considered an acknowledged benchmark in nonlinear system identification.). Less known at first than Mamdami fuzzy controllers, Sugeno fuzzy controllers became popular once they were included into the ANFIS neuro-fuzzy Matlab library. By their nature, Sugeno controllers can be regarded as interpolation…
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…
Adaptive neuro-fuzzy inference system for kinematics solutions of redundant robots
2016
This written paper presents aspects concerning the implementation of the Adaptive Neuro-Fuzzy Inference System (ANFIS) in the resolution of a redundant serial robot kinematics. The kinematics solutions are divided into two categories: direct kinematics solutions and inverse kinematics solutions. To be able to control a robot the most important solutions are the ones for the inverse kinematics since one knows the position and the final orientation of the end effector and needs to determine the relative displacement or movements into the robot couplings. To obtain the optimal solutions for the inverse kinematics of a redundant robot the mathematical equations were based onto the redundancy ci…
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…
An FPGA-Based Adaptive Fuzzy Coprocessor
2005
The architecture of a general purpose fuzzy logic coprocessor and its implementation on an FPGA based System on Chip is described. Thanks to its ability to support a fast dynamic reconfiguration of all its parameters, it is suitable for implementing adaptive fuzzy logic algorithms, or for the execution of different fuzzy algorithms in a time sharing fashion. The high throughput obtained using a pipelined structure and the efficient data organization allows significant increase of the computational capabilities strongly desired in applications with hard real-time constraints.
Longitudinal Study on Sustained Attention to Response Task (SART): Clustering Approach for Mobility and Cognitive Decline
2022
The Sustained Attention to Response Task (SART) is a computer-based go/no-go task to measure neurocognitive function in older adults. However, simplified average features of this complex dataset lead to loss of primary information and fail to express associations between test performance and clinically meaningful outcomes. Here, we combine a novel method to visualise individual trial (raw) information obtained from the SART test in a large population-based study of ageing in Ireland and an automatic clustering technique. We employed a thresholding method, based on the individual trial number of mistakes, to identify poorer SART performances and a fuzzy clusters algorithm to partition the da…
Fixed point theorems for fuzzy mappings and applications to ordinary fuzzy differential equations
2014
Abstract Ran and Reurings (Proc. Am. Math. Soc. 132(5):1435-1443, 2004) proved an analog of the Banach contraction principle in metric spaces endowed with a partial order and discussed some applications to matrix equations. The main novelty in the paper of Ran and Reurings involved combining the ideas in the contraction principle with those in the monotone iterative technique. Motivated by this, we present some common fixed point results for a pair of fuzzy mappings satisfying an almost generalized contractive condition in partially ordered complete metric spaces. Also we give some examples and an application to illustrate our results. MSC:46S40, 47H10, 34A70, 54E50.
Weakly algebraizable logics
2000
AbstractIn the paper we study the class of weakly algebraizable logics, characterized by the monotonicity and injectivity of the Leibniz operator on the theories of the logic. This class forms a new level in the non-linear hierarchy of protoalgebraic logics.
Fuzzy C-Means Segmentation on Brain MR Slices Corrupted by RF-Inhomogeneity
2007
Brain MR Images corrupted by RF-Inhomogeneity exhibit brightness variations in such a way that a standard Fuzzy C-Means (fcm) segmentation algorithm fails. As a consequence, modified versions of the algorithm can be found in literature, which take into account the artifact. In this work we show that the application of a suitable pre-processing algorithm, already presented by the authors, followed by a standard fcm segmentation achieves good results also. The experimental results ones are compared with those obtained using SPM5, which can be considered the state of the art algorithm oriented to brain segmentation and bias removal.