In this paper, the design of a stable direct adaptive neural controller based on single auto-tuning neuron for nonlinear systems is developed. Unlike traditional multi-layered neural controller, the structure of the proposed controller is simpler and practical. Only a single neuron with three adjustable parameters is employed in our proposed neural controller. The adaptation law to adjust these parameters is proposed based on the Lyapunov approach. Moreover, the stability of the system can be also analyzed and guaranteed by introducing the supervisory controller and the modified adaptation law with projection. Such a controller design is very easy for hardware implementation due to its simple structure. Finally, the simulations of an unstable nonlinear system by using the proposed single auto-tuning neural controller will be illustrated to demonstrate the excellent control capability.