Orbital transfer utilizing Hall-effect thrusters (HETs) faces significant challenges due to inherent thrust instabilities and nonlinear actuator faults. This study presents a novel application of an optimized Type‑2 neuro‑fuzzy controller specifically designed to ensure robust maneuvering under severe uncertainty. Unlike prior studies that are primarily restricted to mild fault conditions and limited controller comparisons, the proposed approach is systematically evaluated against a Type‑1 neuro‑fuzzy controller and a conventional linear quadratic regulator. A neural network initializes the control structure, while a genetic algorithm is used solely for fuzzy rule reduction and acceleration of the training process, thereby improving computational efficiency without direct controller tuning. Numerical simulations demonstrate that, under sustained high‑amplitude and high‑frequency fault scenarios, the proposed Type‑2 controller preserves accurate orbital tracking and system stability. In contrast, the comparative methods exhibit significant performance degradation. These results establish a reliable and fault‑tolerant control framework for low‑Earth orbit missions in which conventional robust control strategies prove inadequate.

In contrast, the comparative methods exhibit significant performance degradation. These results establish a reliable and fault‑tolerant control framework for low‑Earth orbit missions in which conventional robust control strategies prove inadequate.