A correlation-based controller tuning method is proposed for the \Design and optimization of restricted-complexity controllers" benchmark problem. The approach originally proposed for model following is applied to solve the disturbance rejection problem. The idea is to tune the controller parameters such that the closed-loop output be uncorrelated with the measured disturbance. Since perfect decorrelation between the closed-loop output and the disturbance is not attainable with a restricted-complexity controller, the cross-correlation of these two signals is minimized. This is done iteratively using stochastic approximation. A frequency analysis of the tuning criterion allows dealing with control speci cations expressed in terms of constraints on the sensitivity functions. Application to the active suspension system of the Automatic Laboratory of Grenoble (LAG) provides a 2nd-order controller that meets the control speci cations to a large extent.