Fuzzy logic and neural networks in space applications
Yashvant Jani, Jack Aldridge · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
Neural networks known for almost a half-century deal with the complexities of the natural world data by generalizing from prototypes or samples in much the same as humans extrapolate from one experience to similar situations. Neural networks have been studied for fault diagnosis and health monitoring of space operations and have been extended to include time correlated data and create the Space-Time Neural Network. Neural networks have been combined with fuzzy logic to investigate the adaptive decision making systems for translational and rotational control. In this paper, we describe some of the space applications of fuzzy logic and neural networks including tether skip-rope identification using Space-Time Neural Network. We also describe the tools developed at Johnson Space Center to support such investigations.