Nowadays, inexpensive memory has led to large router buffers in the Internet, leading to excessively long queues and high latency. This phenomenon is recently termed as “bufferbloat.” Recently, Controlled Delay (CoDel) has been proposed as an active queue management (AQM) algorithm to address this problem by setting a limit (i.e., a target delay) on the queueing delay. However, such a target delay is fixed, and CoDel is thus unable to adapt to changes in the network environment. In this paper, we propose a framework to adaptively control the target delay with changing network conditions, so as to overcome bufferbloat. Specifically, we first develop a theoretical model to analyze the stability of CoDel and derive the stable range of the target delay using control theory. We then propose Adaptive CoDel, which dynamically selects an optimal value of the target delay in the stable range, such that the aggregate TCP goodput is maximized, while keeping the system stable. Our simulation results show that Adaptive CoDel not only effectively controls the queueing delay, but also achieves higher aggregate TCP goodput compared to other AQM algorithms.