Adaptive PID control of an AGV system using humoral immune algorithm and neural network identifier technique

We propose an adaptive PID control method based on humoral immune algorithm (HIA) and neural network identifier (NNI) technique. It is also applied for an autonomous guided vehicle (AGV) system. When HIA is applied to PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use NNI technique for modeling the plant and HIA which performs the parameter tuning of the considered model, respectively. Moreover, even though the neural network model may not be accurate enough initially, and the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the experimental results for the control of steering and speed of AGV system illustrate the effectiveness of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.