The main goal of this paper is to develop a novel approach for achieving a high-performance active piezoelectric absorber of a smart panel using adaptive networks in hierarchical fuzzy control. Due to the adaptive capability of fuzzy inference systems, its applications to adaptive control and learning control are immediate. For this purpose, the adaptive network-based fuzzy inference system has been used to optimize the fuzzy IF-THEN rules and the membership functions to derive a more efficient fuzzy control. Furthermore, the study addresses the application of the concept of hierarchy for controlling fuzzy system to minimize the size of the rule base by eliminating ''the curse of dimensionality''. The computational complexity in the process can be reduced as a consequence of the rule-based size reduction, which has become one of the main concerns among system designers. The main advantage of the hierarchical structure is a great reduction of memory demand in the implementation. Consequently, the proposed controller in this research combines the strength of fuzzy systems, the ability to deal with uncertainties, with the advantage of neural nets, the ability to learn.