A fault-tolerant adaptive quantized control algorithm is developed for strict-feedback nonlinear systems with uncertainties. The design of the controller follows the backstepping process. The unknown nonlinearities in the system are estimated by applying fuzzy logic systems, and a new unified compensation method is developed to handle the control quantization and actuator faults simultaneously. The total count of learning parameters is reduced to just one by further applying the bound estimation technique, which achieves a considerable computational complexity reduction. The semi-global uniform ultimate boundedness (SGUUB) is confirmed in the stability analysis process, and the effectiveness of the quantized control design is demonstrated through numerical simulation.