A self-tuning algorithm for PID controller based on adaptive interaction approach efficiently used in the Artificial Neural Networks (ANNs) is proposed in this paper. The principle behind the adaptation algorithm is mathematically isometric to the back-propagation algorithm (BPA). By applying Adaptive Interaction (AI), the same adaptation as the well-known BPA can be achieved without the need of a feed-back network. Hereby, by using AI tuning algorithm, the ANN PID controller can be adapted directly without wasting calculation time in order to increase the frequency response of the controller. Speed control of a DC motor under the rapidly changing load condition is simulated to demonstrate the sensitivity of the AI algorithm. PID gains of the ANN controller was tuned directly by using AI tuning algorithm. Simulation results and PID adaptation process have been presented.