Fuzzy rule-based pert applied on training/learning planning

Fuzzy modelling and control is a technique to handle qualitative information in a formal, rigorous and efficient way, if such information is properly used. In this paper it is presented an alternative fuzzy logic rule-based method to evaluate the competence of a trainee group subjected to a training/learning process. The developed algorithm for decision on the controlled variable (the product quality), is based on the knowledge of the processing task defined on the basis of an extensive fuzzy rule-base, by measuring the input variables (most likely time). Such algorithm exploits the knowledge of a fuzzy rule-base achieved under the experience of human expert instructors, to be defuzzified by means of a least squares method. The input variables to the rule base are the the time for acquiring skill and knowledge, which results from training/learning task. The rule-base outputs are the inputs to a task planning, solved by means of a pert, controlled in closed-loop feedback and feedforward modes, as a novel contribution