Inspired by observing the similarity between adaptive control systems and recurrent neural networks (RNNs), a new control scheme, the recurrent adaptive control (RAC), is presented in this paper. Back propagation through time (BPTT), a learning algorithm for RNNs, can be exploited in RAC. Application of truncated BPTT to RAC is also discussed. Further, a new control algorithm for RAC, termed recursive gradient (RG), is developed to improve the performance of the original and truncated BPTT algorithms. Effectiveness of the RG control algorithm as a power system stabilizer is demonstrated.