Active queue management (AQM) is an effective method to improve the performance of end-to-end congestion control. Several AQM schemes have been proposed to provide low delay and low loss service in best-effort networks in recent studies, such as RED, PI, REM, AVQ, PD, SMVS and PIP. Among them, PIP is the fusion of PI controller and position feedback compensation and shows better performance under most network conditions, but its parameters can not change with the environments. Based on adaptive single-neuron PID controller, an adaptive PIP AQM scheme is developed using square error of queue length as performance criteria to consolidate the advantages of single neuron and PIP controller. Verified by using NS-2 simulations under a variety of network and traffic situations, the adaptive PIP can achieve faster convergence speed and smaller queue oscillation than PIP, PI, ARED and SPI(self-configuring PI, which is an improved algorithm of PI). In addition, the adaptive scheme can also be used in PI, REM, AVQ, and PD schemes and offers the possibility of optimizing these AQM schemes.