This paper proposes two kinds of fuzzy abductive inference in the framework of fuzzy rule base. The abductive inference processes described here depend on the semantic of the rule. We distinguish two classes of interpretation of a fuzzy rule, certainty generation rules and possible generation rules. In this paper we present the architecture of abductive inference in the first class of interpret...

This paper presents the similarity of a class of adaptive fuzzy controllers and a time dependent single rule controller of TakagiSugeno (TS) model. The class of adaptive fuzzy controllers is one of iterative multilayer structure of single input fuzzy controllers (SIFC). On the other hand, in a time dependent single rule controller of TS model, only one rule can be fired at a time. The result mo...

We propose a general scheme of collective choice rule that covers a number of well-known rules. Our point of departure is, first, the set of fuzzy preference relations, and second, the linguistic aggregation rule proposed by Kacprzyk [2-4]. We reconsider this rule on a more abstract level and use the OWA operators instead of Zadeh’s fuzzy linguistic quantifiers. All collective choice rules from...

This paper proposes a rule selection method with the destructive learning algorithm to construct a compact fuzzy classification system with high performance. In this paper, first we construct a fuzzy classification system by generating fuzzy rules from numerical data, and consider the fuzzy classification system based on fuzzy rules a network. Then we select significant fuzzy rules from the rul...

An on-line rule tuning grey prediction fuzzy control system is present in this paper, which contains the advantage of the grey prediction, fuzzy theory and the on-line tuning algorithm. The on-line rule tuning grey prediction fuzzy control system structure is constructed so that the rise time and the overshoot of the controlled system can be maintained simultaneously. Keyword: Grey predictor, F...

This paper introduces, in analogy to the concept of fuzzy numbers, the concept of fuzzy booleans, and examines approximate reasoning with the compositional rule of inference using fuzzy booleans. It is shown that each set of fuzzy rules is equivalent to a set of fuzzy rules with singleton crisp antecedents; in case of fuzzy booleans this set contains only two rules. It is shown that Zadeh's ext...

It is well known that a fuzzy rule base is a characterization of a partially given mapping (fuzzy function) between fuzzy universes. For practical applications, it is desirable to interpolate that function in order to compute its values at points (fuzzy or crisp) other than fuzzy sets (nodes) in antecedents of the rule base. Moreover, interpolation requires that in the case of coincidence betwe...

In this study, the roll, yaw and depth fuzzy control of an Au- tonomous Underwater Vehicle (AUV) are addressed. Yaw and roll angles are regulated only using their errors and rates, but due to the complexity of depth dynamic channel, additional pitch rate quantity is used to improve the depth loop performance. The discussed AUV has four aps at the rear of the vehicle as actuators. Two rule bases...

The fuzzy rule based inference is known to be a useful tool to capture the behavior of an approximate system in transportation. One of the obstacles of implementing the fuzzy rule based inference, however, has been to calibrate the membership functions of the fuzzy sets used in the rules. This paper proposes a way to calibrate the membership function when a set of input and output data is given...