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Vapor compression systems form the basis for the majority of air conditioning and refrigeration systems. A primary control challenge addressed here is the coupled nonlinear multiple-input-multiple-output (MIMO) dynamics associated with the multiphase heat and mass transfer in the primary refrigerant loop. This paper develops a MIMO gain scheduled control strategy to regulate system efficiency while meeting changing demands for cooling capacity. An approach based on the Youla parameterization is shown to be a generalization of the more common local controller network method, while exposing several degrees of design freedom that can be exploited to improve stability. The challenge of guaranteeing stability of the nonlinear closed loop systems, despite endogenous and arbitrarily fast gain scheduling, is addressed. Experimental results confirm the effectiveness of the proposed approach.