Recognizing that Internet congestion control is a complex nonlinear system, we propose here to use an intelligent controller to improve its stability and performance. In particular, we propose here a new, powerful, easy-to-configure and robust active queue management (AQM) scheme called adaptive neuron AQM (AN-AQM). We present extensive simulation results for AN-AQM, over a wide range of network conditions and scenarios, that demonstrate its attributes. We demonstrate its robustness in various realistic environments involving bursty HTTP connections and non-responsive UDP connections. Comparison with other AQM schemes has demonstrated the superiority of AN-AQM over well-known AQM schemes in achieving faster convergence to queue length target, and smaller queue length jitter.