This paper proposes a parallel architecture of random signal-based learning (PRSL), merged with simulated annealing (SA), to optimize the fuzzy logic controller (FLC). Random signal-based learning (RSL) finds the local optima very well, whereas it can not finds the global optimum in a very complex search space because of its serial nature. To overcome these difficulties, PRSL, which consists of serial RSL as a population, is considered. Moreover, SA is added to RSL to help the exploration. The validity of the proposed algorithm is conformed by applying it to the optimization of a FLC for the inverted pendulum.