Keywords: Genetic Algorithm, Multi-objective Optimization, Fuzzy Logic Controller. Abstract: A Takagi-Sugeno (T-S) Fuzzy Logic Controller (FLC) is tuned using the algorithm NSGA-II. The proposed method eliminates laborious design steps such as tuning of membership functions and conclusion table parameters. An object approach representation is used to build an adequate FLC representation. Object is an individual abstraction in order to improve crossover a mutation operators. The Genetic Algorithm optimization is carry out over signal response performance parameters, in this work: settling time, rise time, overshoot and steady state error. Experiments show how the algorithm reached good response of some individuals in solution set, typically called Pareto frontier.