The paper presents Fuzzy Logic Controllers (FLC) with hierarchically structured rule base as nonlinear blocks used in a control system for direct control or supervision of standard controllers. Unified approach based on Fuzzy Logic Neural Networks (FLNN) is used to reveal the essential functions of a FLC. The FLNN is then extended to the case where decomposition of a rule base leads to simplification of controller design and tuning. Two structures of hierarchically organized groups of rules are discussed. Singlestage decision making structure with groups of rules organized hierarchically according to their specificity and a multi-stage decision making architecture with chained rules. Data induced error backpropagation technique for fine tuning of parameters of the second structure is derived.