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This paper introduces a fuzzy neural based adaptive controller for simultaneous stabilization and robust performance of a family of plants. The family of plants may be attained from linearization of a nonlinear plant around different operating points or large parameter variations in a given plant. The main idea is to design a sequence of controllers corresponding to the different plants utilizing any standard control design. Thereafter, the obtained controllers will form the basis of the knowledge base of a fuzzy controller capable of deriving a desired crisp output through its inference engine. A neural network is utilized to derive a fuzzy model of the plant and to generate the rule base for the fuzzy logic controller through training. The effectiveness of this new scheme is verified on a smart structure with piezoceramic sensors and actuators.