Fuzzy Control Strategies in Human Operator and Sport Modeling
Tijana T. Ivancevic, Bojan Jovanovic, and Sasa Markovic
TL;DR
This paper introduces fuzzy logic control strategies, including fixed and adaptive methods, for modeling human operators and sports activities, demonstrated through a tennis simulator to better understand complex human-system interactions.
Contribution
It presents novel fuzzy logic control approaches, such as neuro-fuzzy-fractal control, for human and sports modeling, with practical application in a tennis simulation.
Findings
Effective fuzzy-control tennis simulator developed
Demonstrated adaptability of fuzzy logic strategies
Enhanced understanding of human operator response characteristics
Abstract
The motivation behind mathematically modeling the human operator is to help explain the response characteristics of the complex dynamical system including the human manual controller. In this paper, we present two different fuzzy logic strategies for human operator and sport modeling: fixed fuzzy-logic inference control and adaptive fuzzy-logic control, including neuro-fuzzy-fractal control. As an application of the presented fuzzy strategies, we present a fuzzy-control based tennis simulator.
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Taxonomy
TopicsTime Series Analysis and Forecasting · Anomaly Detection Techniques and Applications · Neural Networks and Applications