In this paper, a novel adaptive general type-2 fuzzy model-based control (AGT2-FMBC) is proposed for networked control systems (NCSs) with packet dropouts. A general type-2 fuzzy model (GT2FM) is designed to represent the nonlinear system with uncertainties online, wherein the antecedents of fuzzy rules are defined by general type-2 fuzzy sets and the consequents by Takagi-Sugeno type models. Utilizing the Bernoulli distribution, packet dropouts in the two communication channels are effectively modeled. To mitigate their negative effect, we introduce buffers at the input of both the controller and the nonlinear system. A general type-2 fuzzy controller (GT2FC) is proposed to achieve optimal tracking performance based on the parallel distributed compensation approach. The GT2FC shares the same antecedent parts with the GT2FM, while its consequent parts serve as local inverse model controllers for corresponding consequent parts of the GT2FM. To reduce computation time in the type-reducer, a direct defuzzification method is utilized, introducing two factors to determine the participation of the lower and upper bounds. We introduce a novel algorithm to provide adaptive online laws for the parameters of AGT2-FMBC, ensuring convergence through the Lyapunov stability theorem. The robustness of the proposed controller is demonstrated through its application to three nonlinear NCSs, subject to packet dropouts and uncertainties.