<p>This article investigates the issue of global exponential lag projective synchronization in a fractional-order fuzzy neural network with time delays. Such networks exhibit considerable potential in modeling complex nonlinear systems, owing to their capacity to integrate fractional calculus, fuzzy logic, and neural network characteristics. However, the presence of time delays in these networks tends to complicate the synchronization process, posing challenges to the stability and performance of associated dynamic systems. To tackle this issue, this study first proposes two types of hybrid controllers. Subsequently, by incorporating properties of differential equations, stability theory, the direct Lyapunov method, the Razumikhin theorem, and advanced inequality techniques, sufficient conditions for achieving such synchronization are rigorously derived. These conditions effectively guarantee the achievement of global exponential lag projective synchronization in the considered neural networks. Finally, numerical simulations are performed. The results not only verify the feasibility of these theoretical findings but also illustrate the validity of the proposed controllers and methodologies in practical scenario.</p>