PubMed Health⌕ Search

PubMed · 7598656

Fuzzy control concept for a total artificial heart.

Abstract

The development of an electromechanically driven total artificial heart (Helmholtz-TAH) was initiated in 1990. Anatomical fitting, biocompatibility, and automatic physiologic adaptation of pump output are the basic requirements that characterize the overall TAH concept. For evaluation of these features, a TAH labtype was developed. It provides most features of the conceptual artificial heart and supports in vitro testing of energy conversion, pump behavior, structural parts, sensors, and control concepts. A fuzzy controller has been implemented for adaptation of the pump rate to body perfusion demand by left pump chamber filling detection. This controller will be an important element of a future extensive TAH control system. The implementation is supported by a professional fuzzy control development tool that allows on-line and real time optimization of control strategies for dynamic processes. The first experiments proved the feasibility and the advantages of this fuzzy control concept. The first in vitro test results are presented.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

R Kaufmann, K Becker, C Nix, H Reul, G Rau. 1995. Fuzzy control concept for a total artificial heart.. https://doi.org/10.1111/j.1525-1594.1995.tb02340.x

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Advanced fuzzy cellular neural network: application to CT liver images.

OBJECTIVE: To achieve better boundary integrities and recall accuracies for segmented liver images, use of the advanced fuzzy cellular neural network (AFCNN), as a variant of the fuzzy cellular neural network (FCNN), is proposed to effectively segment CT liver images. MATERIALS AND METHODS: In order to better utilize relevant contour and gray information from liver images, we have improved the FCNN [Wang S, Wang M. A new algorithm NDA based on fuzzy cellular neural networks for white blood cell detection. IEEE Trans Inform Technol Biomed, in press], which proved to be very effective for the segmentation of microscopic white blood cell images, to create the novel neural network, AFCNN. Its convergent property and global stability are proved. Based on the FCNN-based NDA algorithm [Wang S, Wang M. A new algorithm NDA based on fuzzy cellular neural networks for white blood cell detection. IEEE Trans Inform Technol Biomed, in press], we developed the AFCNN-based NDA algorithm, which we used to segment 5 CT liver images. For comparison, we also segmented the same 5 CT liver images using the FCNN-based NDA algorithm. RESULTS AND CONCLUSION: : AFCNN has distinct advantages over FCNN in both boundary integrity and recall accuracy. In particular, the performance index Binary_rate is generally much higher for AFCNN than for FCNN when applied to CT liver images.

Fuzzy Logic↗

Experimental percolation under intermittent conditions: influence on pollutants emission from waste.

As a precautionary measure, the re-use (or landfill) of waste requires an environmental assessment of its potential impact. This assessment is usually made by simulating the emission of pollutants with a predictive model based on laboratory tests (standardised batch leaching tests, up-flow percolation tests, acid neutralisation capacity tests [CEN, Characterisation of Waste--Leaching--Compliance Test for Leaching of Granular Waste Materials and Sludges, European Committee for Standardisation (ECS), Brussels, 2002 ; CEN, prCEN/TS 14405 Characterisation of Waste--Leaching Behaviour Tests--Up-flow Percolation Test (under specified conditions), ECS, Brussels, 2002 ; CEN, prCEN/TS 14429 Characterisation of Waste--Leaching Behaviour Test--Influence of pH on Leaching with Initial Acid/base Addition, ECS, Brussels, 2003 ]. These tests are performed with simpler conditions than those occurring in the scenario of re-use (saturated media, permanent inflow ...). In order to evaluate the relevance of these tests to be considered as a reference for predictive model, the purpose of this work is to determine how the intermittent hydrodynamic flow influences the pollutants release of unsaturated waste. As a result, we could estimate whether this parameter should be introduced in the model.

Fuzzy Logic↗

Comparison of neurofuzzy logic and neural networks in modelling experimental data of an immediate release tablet formulation.

This study compares the performance of neurofuzzy logic and neural networks using two software packages (INForm and FormRules) in generating predictive models for a published database for an immediate release tablet formulation. Both approaches were successful in developing good predictive models for tablet tensile strength and drug dissolution profiles. While neural networks demonstrated a slightly superior capability in predicting unseen data, neurofuzzy logic had the added advantage of generating rule sets representing the cause-effect relationships contained in the experimental data.

Fuzzy Logic↗