<p>The synchronization and control of financial chaotic/hyperchaotic systems (FCS) are studied in this paper. The FCS are advanced tools to analyze the modern financial systems. These systems exhibit nonlinear behaviour due to interactions between various market participants and uncertainties, where small changes usually lead to disproportionately large effects. While chaos theory provides an effective way to model the market behavior, effectively managing, synchronizing, and controlling these systems requires an advanced control approach that combines modern modeling techniques, behavioral analysis, and robust control systems. In this paper, a hybrid control system is introduced to deal with the complex and highly uncertain dynamics of FCSs along with multiple disturbances and delays. First, a new type-3 (T3) fuzzy system (FS) is developed for discrete-time modeling of FCSs’s unknown dynamics and disturbances. Based on T3-FS modeling, a primary controller is designed. Then, a feedback control law is designed to establish robust performance in the presence of approximation errors and delays, promoting performance under varying conditions. Finally, based on linear matrix inequality (LMI) and the Lyapunov theorem, sufficient conditions are derived to stabilize FCS’s closed loop. Online training of the T3-FS model allows the designed controller to adapt to varying conditions and uncertainties in real-time. The asymptotic stability ensures that the trajectories are converted to the target setpoint and the desired synchronization is achieved. Several simulations are conducted to evaluate the synchronization and control performance.</p>