In this paper, we aim at developing computationally tractable methods for nonlinear model/controller reduction. Recently, model reduction by generalized differential (GD) balancing has been proposed for nonlinear systems with constant input-vector fields and linear output functions. First, we study incremental properties in the GD balancing framework. Next, based on these analyses, we provide GD LQG balancing and GD H∞-balancing as controller reduction methods for nonlinear systems by focusing on linear feedback and observer gains. Especially for GD H∞-balancing, we clarify when the closedloop system consisting of the full-order system and a reducedorder controller is exponentially stable. All provided methods for controller reduction can be relaxed to linear matrix inequalities.