In this paper, the general problem of identifying the parameters describing Sugeno controllers from example data is addressed. It is shown that this approximation is ill-posed, which necessitates the use of regularization methods. Based upon this discovery, an efficient numerical algorithm for solving the general regularized approximation problem is proposed, followed by numerical examples with real-world data.