Automatic and antiskid braking systems are primary requirements for new aircraft designs, specially airliners, because of the massive kinetic energy to be dissipated during landing or a reject take-off maneuver. To ensure the best braking performance, the friction coefficient between tire and road should be held at the maximum value. However, this parameter depends on the tire slip ratio and the road conditions. Thus, to accomplish a efficient braking maneuver, the braking control system should ensure that the slip ratio is in a optimum value for each road type. This project proposes the application of a digital PID controller to the nonlinear aircraft model. A landing gear motion model with actuation and tire curves is used in the simulation for the controller design. Then, a optimization using two evolutionary algorithms is made in order to determine the controller parameters. As a result, the particle swarm optimization and the genetic algorithm converged to a optimum controller after the implementation of a cost function able to penalize unstable solutions.