Fuzzy control of robot manipulators:: some issues on design and rule base size reduction
This paper is aimed at looking into the automatic design and the size reduction of the rule base of fuzzy logic controllers. The first part is concerned with an automatic generation method of the fuzzy rule base. This is done by the use of an intelligent optimization method, and its implementation to the design of a fuzzy controller for robot manipulators. It is assumed that such system is known but ill-defined because of the inherent uncertainties associated with the model. Thus, an accurate mathematical model is not required, but a simplified one is acceptable. The second part treats the reduction of large scale fuzzy rule bases. Two approaches are used for this purpose: the boolean method and the decoupling approach giving a local control loop yielding smaller fuzzy controllers. The boolean approach is based on the equivalence between fuzzy preconditions and on boolean expressions. Using the fact that fuzzy sets are a generalization of classical subsets, we introduced some operations on fuzzy sets that are equivalent to those applied in the boolean logic approach. The paper then discusses the reduction of large scale fuzzy rule bases by the use of a decoupling approach, and its application to the case of an optimal fuzzy logic controller of a three-links robot manipulator using local PID controllers.
robot manipulator rule base size reduction fuzzy logic optimization decoupling approach