To avoid linear model redundancy and simplify the structure of a multimodel controller, two general integrated multimodel control design frameworks, which integrate the multimodel decomposition and the multimodel combination of a nonlinear system, are proposed based on the gap metric and stability margin criteria. One method uses the maximum stability margin (which is comparatively controller-independent) while the other uses the actual stability margin of a given controller design. For a prescribed linear control algorithm for local controller design, a smaller and better linear model bank that provides necessary information for multimodel controller design is obtained systematically without model redundancy. Besides, the local robust stability and performance of the system in each subregion can be achieved by the corresponding local controller. Many linear control techniques can be used in the proposed design frameworks, and H-infinity control algorithm is employed as an example and applied to two benchmark nonlinear chemical processes for set point tracking and disturbance rejection control. Closed-loop simulations demonstrate that the proposed approaches are both systematic and effective and are better than the traditional multimodel control methods in terms of robust performance.