Uncertainty Treatment for Intelligent Systems - A Neurocomputing Alternative

ABSTRACT The state of health of a structure, with control devices, can be assessed from sensor measure­ ments, but its estimate is very sensitive to any sort of uncertainty. This paper investigates the potentialities offered by neural computing for building a different way of manipulating sensor measurements. The main goals are: 1) to avoid mathematical models for the definition , in the state variable space, of the region where the actuators may remain inactive; 2) to give the system control ’brain’ the possibility of learning from the experience of service.