This article proposes an adaptive constrained control considering input saturation and prescribed performance constraints for uncertain two-degree-of-freedom helicopter systems with actuator faults. A devised performance function precisely indicates the time for the system to achieve stability and adjusts the convergence speed of its dynamic process through parameter modifications. The smoothing Gaussian error function is introduced to replace the saturated nonlinearity of each nonsmooth actuator, the radial basis function neural network is employed for approximating the unknown nonlinear function, adaptive auxiliary parameters are introduced, and an adaptive controller is designed to address issues, such as model uncertainty, input saturation, and actuator faults arising in practical applications. Furthermore, the Lyapunov direct method is employed to demonstrate the stability and boundedness of the helicopter system. Results obtained from simulations and experiments on the Quanser two-degree-of-freedom helicopter experimental platform confirm the effectiveness and feasibility of the proposed control method.