In this paper, an adaptive fuzzy controller design methodology via MultiObjective Particle Swarm Optimization (MOPSO) based on robust stability criterion, is proposed. The plant to be controlled is modeled from its input-output experimental data considering a Takagi-Sugeno (TS) fuzzy NARX model, by using the fuzzy C-Means clustering algorithm (antecedent parameters estimation) and Weighted Recursive Least Squares (WRLS) algorithm (consequent parameters estimation). An adaptation mechanism as MOPSO problem for online tuning of a fuzzy model based digital PID controller parameters, based on the gain and phase margins specifications, is formulated. Experimental results for adaptive fuzzy digital PID control of a thermal plant with time varying delay is presented to illustrate the efficiency and applicability of the proposed methodology.